MANAO - 2023

2023Activity reportProject-TeamMANAO

RNSR: 201221025F
  • Research center Inria Centre at the University of Bordeaux
  • In partnership with:Université de Bordeaux, CNRS
  • Team name: Melting the frontiers between Light, Shape and Matter
  • In collaboration with:Laboratoire Bordelais de Recherche en Informatique (LaBRI)
  • Domain:Perception, Cognition and Interaction
  • Theme:Interaction and visualization


Computer Science and Digital Science

  • A5. Interaction, multimedia and robotics
  • A5.1.1. Engineering of interactive systems
  • A5.1.6. Tangible interfaces
  • A5.3.5. Computational photography
  • A5.4. Computer vision
  • A5.4.4. 3D and spatio-temporal reconstruction
  • A5.5. Computer graphics
  • A5.5.1. Geometrical modeling
  • A5.5.2. Rendering
  • A5.5.3. Computational photography
  • A5.5.4. Animation
  • A5.6. Virtual reality, augmented reality
  • A6.2.3. Probabilistic methods
  • A6.2.5. Numerical Linear Algebra
  • A6.2.6. Optimization
  • A6.2.8. Computational geometry and meshes

Other Research Topics and Application Domains

  • B3.1. Sustainable development
  • B3.1.1. Resource management
  • B3.6. Ecology
  • B5. Industry of the future
  • B5.1. Factory of the future
  • B9. Society and Knowledge
  • B9.2. Art
  • B9.2.2. Cinema, Television
  • B9.2.3. Video games
  • B9.6. Humanities
  • B9.6.1. Psychology
  • B9.6.6. Archeology, History
  • B9.6.10. Digital humanities

1 Team members, visitors, external collaborators

Research Scientists

  • Pascal Barla [Team leader, INRIA, Researcher, HDR]
  • Gael Guennebaud [INRIA, Researcher]
  • Romain Pacanowski [INRIA, Researcher, HDR]

Faculty Members

  • Pierre Benard [UNIV BORDEAUX, Associate Professor]
  • Patrick Reuter [UNIV BORDEAUX, Associate Professor, HDR]

Post-Doctoral Fellows

  • Jean Basset [INRIA, Post-Doctoral Fellow, from Feb 2023]
  • Morgane Gerardin [INRIA, Post-Doctoral Fellow, until Jun 2023]
  • Pierre Mezieres [INRIA, Post-Doctoral Fellow, from Jul 2023]

PhD Students

  • Corentin Cou [CNRS]
  • Melvin Even [INRIA]
  • Gary Fourneau [INRIA]
  • Pierre La Rocca [UNIV BORDEAUX]
  • Simon Lucas [UNIV BORDEAUX]
  • Lea Marquet [INRIA, from Nov 2023]
  • Panagiotis Tsiapkolis [UBISOFT, CIFRE]

Technical Staff

  • Marjorie Paillet [INRIA, Engineer, until Oct 2023]

Interns and Apprentices

  • Pablo Leboulanger [UNIV BORDEAUX, Intern, from Mar 2023 until Jul 2023]
  • Bastien Morel [INRIA, Intern, from Mar 2023 until Aug 2023]
  • Coralie Rigaut [INRIA, Intern, from Feb 2023 until Jul 2023]

Administrative Assistant

  • Anne-Laure Gautier [INRIA]

External Collaborators

  • Aurelie Bugeau [UNIV BORDEAUX, from Sep 2023, HDR]
  • Morgane Gerardin [UNIV TOULOUSE III, from Jul 2023]
  • Xavier Granier [UNIV PARIS SACLAY, HDR]

2 Overall objectives

2.1 General Introduction

Computer generated images are ubiquitous in our everyday life. Such images are the result of a process that has seldom changed over the years: the optical phenomena due to the propagation of light in a 3D environment are simulated taking into account how light is scattered  61, 38 according to shape and material characteristics of objects. The intersection of optics (for the underlying laws of physics) and computer science (for its modeling and computational efficiency aspects) provides a unique opportunity to tighten the links between these domains in order to first improve the image generation process (computer graphics, optics and virtual reality) and next to develop new acquisition and display technologies (optics, mixed reality and machine vision).

Most of the time, light, shape, and matter properties are studied, acquired, and modeled separately, relying on realistic or stylized rendering processes to combine them in order to create final pixel colors. Such modularity, inherited from classical physics, has the practical advantage of permitting to reuse the same models in various contexts. However, independent developments lead to un-optimized pipelines and difficult-to-control solutions since it is often not clear which part of the expected result is caused by which property. Indeed, the most efficient solutions are most often the ones that blur the frontiers between light, shape, and matter to lead to specialized and optimized pipelines, as in real-time applications (like Bidirectional Texture Functions  71 and Light-Field rendering  36). Keeping these three properties separated may lead to other problems. For instance:

  • Measured materials are too detailed to be usable in rendering systems and data reduction techniques have to be developed  70, 72, leading to an inefficient transfer between real and digital worlds;
  • It is currently extremely challenging (if not impossible) to directly control or manipulate the interactions between light, shape, and matter. Accurate lighting processes may create solutions that do not fulfill users' expectations;
  • Artists can spend hours and days in modeling highly complex surfaces whose details will not be visible  92 due to inappropriate use of certain light sources or reflection properties.

Most traditional applications target human observers. Depending on how deep we take into account the specificity of each user, the requirement of representations, and algorithms may differ.

Examples of new display technologies

Figure1: Examples of new display technologies. Nowadays, they are not limited to a simple array of 2D low-dynamic RGB values.

With the evolution of measurement and display technologies that go beyond conventional images (e.g., as illustrated in Figure 1, High-Dynamic Range Imaging  82, stereo displays or new display technologies  57, and physical fabrication  28, 45, 53) the frontiers between real and virtual worlds are vanishing  41. In this context, a sensor combined with computational capabilities may also be considered as another kind of observer. Creating separate models for light, shape, and matter for such an extended range of applications and observers is often inefficient and sometimes provides unexpected results. Pertinent solutions must be able to take into account properties of the observer (human or machine) and application goals.

2.2 Methodology

Figure 2

Interactions/Transfers between real and virtual worlds.

Figure2: Interactions/Transfers between real and virtual worlds. One of our goal is to combine optical instruments with processes from computer science in order to blend the two worlds.

2.2.1 Using a global approach

The main goal of the MANAO project is to study phenomena resulting from the interactions between the three components that describe light propagation and scattering in a 3D environment: light, shape, and matter. Improving knowledge about these phenomena facilitates the adaption of the developed digital, numerical, and analytic models to specific contexts. This leads to the development of new analysis tools, new representations, and new instruments for acquisition, visualization, and display.

To reach this goal, we have to first increase our understanding of the different phenomena resulting from the interactions between light, shape, and matter. For this purpose, we consider how they are captured or perceived by the final observer, taking into account the relative influence of each of the three components. Examples include but are not limited to:

  • The manipulation of light to reveal reflective  33 or geometric properties  99, as mastered by professional photographers;
  • The modification of material characteristics or lighting conditions  98 to better understand shape features, for instance to decipher archaeological artifacts;
  • The large influence of shape on the captured variation of shading  80 and thus on the perception of material properties  95.

Based on the acquired knowledge of the influence of each of the components, we aim at developing new models that combine two or three of these components. Examples include the modeling of Bidirectional Texture Functions (BTFs)  44 that encode in a unique representation effects of parallax, multiple light reflections, and also shadows without requiring to store separately the reflective properties and the meso-scale geometric details, or Light-Fields that are used to render 3D scenes by storing only the result of the interactions between light, shape, and matter both in complex real environments and in simulated ones.

One of the strengths of MANAO is that we are inter-connecting computer graphics and optics (Figure 2). On one side, the laws of physics are required to create images but may be bent to either increase performance or user's control: this is one of the key advantage of computer graphics approach. It is worth noticing that what is not possible in the real world may be possible in a digital world. However, on the other side, the introduced approximations may help to better comprehend the physical interactions of light, shape, and matter.

2.2.2 Taking observers into account

The MANAO project specifically aims at considering information transfer, first from the real world to the virtual world (acquisition and creation), then from computers to observers (visualization and display). For this purpose, we use a larger definition of what an observer is: it may be a human user or a physical sensor equipped with processing capabilities. Sensors and their characteristics must be taken into account in the same way as we take into account the human visual system in computer graphics. Similarly, computational capabilities may be compared to cognitive capabilities of human users. Some characteristics are common to all observers, such as the scale of observed phenomena. Some others are more specifics to a set of observers. For this purpose, we have identified two classes of applications.

  • Physical systems Provided our partnership that leads to close relationships with optics, one novelty of our approach is to extend the range of possible observers to physical sensors in order to work on domains such as simulation, mixed reality, and testing. Capturing, processing, and visualizing complex data is now more and more accessible to everyone, leading to the possible convergence of real and virtual worlds through visual signals. This signal is traditionally captured by cameras. It is now possible to augment them by projecting (e.g., the infrared laser of Microsoft Kinect) and capturing (e.g., GPS localization) other signals that are outside the visible range. These supplemental information replace values traditionally extracted from standard images and thus lower down requirements in computational power  68. Since the captured images are the result of the interactions between light, shape, and matter, the approaches and the improved knowledge from MANAO help in designing interactive acquisition and rendering technologies that are required to merge the real and the virtual world. With the resulting unified systems (optical and digital), transfer of pertinent information is favored and inefficient conversion is likely avoided, leading to new uses in interactive computer graphics applications, like augmented reality  32, 41 and computational photography  81.
  • Interactive visualization This direction includes domains such as scientific illustration and visualization, artistic or plausible rendering. In all these cases, the observer, a human, takes part in the process, justifying once more our focus on real-time methods. When targeting average users, characteristics as well as limitations of the human visual system should be taken into account: in particular, it is known that some configurations of light, shape, and matter have masking and facilitation effects on visual perception  92. For specialized applications, the expertise of the final user and the constraints for 3D user interfaces lead to new uses and dedicated solutions for models and algorithms.

3 Research program

3.1 Related Scientific Domains

Figure 3

Related scientific domains of the MANAO project

Figure3: Related scientific domains of the MANAO project.

The MANAO project aims at studying, acquiring, modeling, and rendering the interactions between the three components that are light, shape, and matter from the viewpoint of an observer. As detailed more lengthily in the next section, such a work will be done using the following approach: first, we will tend to consider that these three components do not have strict frontiers when considering their impacts on the final observers; then, we will not only work in computer graphics, but also at the intersection of computer graphics and optics, exploring the mutual benefits that the two domains may provide. It is thus intrinsically a transdisciplinary project (as illustrated in Figure 3) and we expect results in both domains.

Thus, the proposed team-project aims at establishing a close collaboration between computer graphics (e.g., 3D modeling, geometry processing, shading techniques, vector graphics, and GPU programming) and optics (e.g., design of optical instruments, and theories of light propagation). The following examples illustrate the strengths of such a partnership. First, in addition to simpler radiative transfer equations  46 commonly used in computer graphics, research in the later will be based on state-of-the-art understanding of light propagation and scattering in real environments. Furthermore, research will rely on appropriate instrumentation expertise for the measurement  58, 59 and display  57 of the different phenomena. Reciprocally, optics researches may benefit from the expertise of computer graphics scientists on efficient processing to investigate interactive simulation, visualization, and design. Furthermore, new systems may be developed by unifying optical and digital processing capabilities. Currently, the scientific background of most of the team members is related to computer graphics and computer vision. A large part of their work have been focused on simulating and analyzing optical phenomena as well as in acquiring and visualizing them. Combined with the close collaboration with the optics laboratory LP2N and with the students issued from the “Institut d'Optique”, this background ensures that we can expect the following results from the project: the construction of a common vocabulary for tightening the collaboration between the two scientific domains and creating new research topics. By creating this context, we expect to attract (and even train) more trans-disciplinary researchers.

At the boundaries of the MANAO project lie issues in human and machine vision. We have to deal with the former whenever a human observer is taken into account. On one side, computational models of human vision are likely to guide the design of our algorithms. On the other side, the study of interactions between light, shape, and matter may shed some light on the understanding of visual perception. The same kind of connections are expected with machine vision. On the one hand, traditional computational methods for acquisition (such as photogrammetry) are going to be part of our toolbox. On the other hand, new display technologies (such as the ones used for augmented reality) are likely to benefit from our integrated approach and systems. In the MANAO project we are mostly users of results from human vision. When required, some experimentation might be done in collaboration with experts from this domain, like with the European PRISM project. For machine vision, provided the tight collaboration between optical and digital systems, research will be carried out inside the MANAO project.

Analysis and modeling rely on tools from applied mathematics such as differential and projective geometry, multi-scale models, frequency analysis  48 or differential analysis  80, linear and non-linear approximation techniques, stochastic and deterministic integrations, and linear algebra. We not only rely on classical tools, but also investigate and adapt recent techniques (e.g., improvements in approximation techniques), focusing on their ability to run on modern hardware: the development of our own tools (such as Eigen) is essential to control their performances and their abilities to be integrated into real-time solutions or into new instruments.

3.2 Research axes

The MANAO project is organized around four research axes that cover the large range of expertise of its members and associated members. We briefly introduce these four axes in this section. More details and their inter-influences that are illustrated in the Figure 2 will be given in the following sections.

Axis 1 is the theoretical foundation of the project. Its main goal is to increase the understanding of light, shape, and matter interactions by combining expertise from different domains: optics and human/machine vision for the analysis and computer graphics for the simulation aspect. The goal of our analyses is to identify the different layers/phenomena that compose the observed signal. In a second step, the development of physical simulations and numerical models of these identified phenomena is a way to validate the pertinence of the proposed decompositions.

In Axis 2, the final observers are mainly physical captors. Our goal is thus the development of new acquisition and display technologies that combine optical and digital processes in order to reach fast transfers between real and digital worlds, in order to increase the convergence of these two worlds.

Axes 3 and 4 focus on two aspects of computer graphics: rendering, visualization and illustration in Axis 3, and editing and modeling (content creation) in Axis 4. In these two axes, the final observers are mainly human users, either generic users or expert ones (e.g., archaeologist  84, computer graphics artists).

3.3 Axis 1: Analysis and Simulation

Challenge: Definition and understanding of phenomena resulting from interactions between light, shape, and matter as seen from an observer point of view.

Results: Theoretical tools and numerical models for analyzing and simulating the observed optical phenomena.

To reach the goals of the MANAO project, we need to increase our understanding of how light, shape, and matter act together in synergy and how the resulting signal is finally observed. For this purpose, we need to identify the different phenomena that may be captured by the targeted observers. This is the main objective of this research axis, and it is achieved by using three approaches: the simulation of interactions between light, shape, and matter, their analysis and the development of new numerical models. This resulting improved knowledge is a foundation for the researches done in the three other axes, and the simulation tools together with the numerical models serve the development of the joint optical/digital systems in Axis 2 and their validation.

One of the main and earliest goals in computer graphics is to faithfully reproduce the real world, focusing mainly on light transport. Compared to researchers in physics, researchers in computer graphics rely on a subset of physical laws (mostly radiative transfer and geometric optics), and their main concern is to efficiently use the limited available computational resources while developing as fast as possible algorithms. For this purpose, a large set of theoretical as well as computational tools has been introduced to take a maximum benefit of hardware specificities. These tools are often dedicated to specific phenomena (e.g., direct or indirect lighting, color bleeding, shadows, caustics). An efficiency-driven approach needs such a classification of light paths  54 in order to develop tailored strategies  96. For instance, starting from simple direct lighting, more complex phenomena have been progressively introduced: first diffuse indirect illumination  52, 88, then more generic inter-reflections  61, 46 and volumetric scattering  85, 43. Thanks to this search for efficiency and this classification, researchers in computer graphics have developed a now recognized expertise in fast-simulation of light propagation. Based on finite elements (radiosity techniques) or on unbiased Monte Carlo integration schemes (ray-tracing, particle-tracing, ...), the resulting algorithms and their combination are now sufficiently accurate to be used-back in physical simulations. The MANAO project will continue the search for efficient and accurate simulation techniques, but extending it from computer graphics to optics. Thanks to the close collaboration with scientific researchers from optics, new phenomena beyond radiative transfer and geometric optics will be explored.

Search for algorithmic efficiency and accuracy has to be done in parallel with numerical models. The goal of visual fidelity (generalized to accuracy from an observer point of view in the project) combined with the goal of efficiency leads to the development of alternative representations. For instance, common classical finite-element techniques compute only basis coefficients for each discretization element: the required discretization density would be too large and to computationally expensive to obtain detailed spatial variations and thus visual fidelity. Examples includes texture for decorrelating surface details from surface geometry and high-order wavelets for a multi-scale representation of lighting  42. The numerical complexity explodes when considering directional properties of light transport such as radiance intensity (Watt per square meter and per steradian - W.m-2.sr-1), reducing the possibility to simulate or accurately represent some optical phenomena. For instance, Haar wavelets have been extended to the spherical domain  87 but are difficult to extend to non-piecewise-constant data  90. More recently, researches prefer the use of Spherical Radial Basis Functions  93 or Spherical Harmonics  79. For more complex data, such as reflective properties (e.g., BRDF  73, 62 - 4D), ray-space (e.g., Light-Field  69 - 4D), spatially varying reflective properties (6D - 83), new models, and representations are still investigated such as rational functions  76 or dedicated models  30 and parameterizations  86, 91. For each (newly) defined phenomena, we thus explore the space of possible numerical representations to determine the most suited one for a given application, like we have done for BRDF  76.

Firts-order analysis

Figure4: First-order analysis   97 have shown that shading variations are caused by depth variations (first-order gradient field) and by normal variations (second-order fields). These fields are visualized using hue and saturation to indicate direction and magnitude of the flow respectively.

Before being able to simulate or to represent the different observed phenomena, we need to define and describe them. To understand the difference between an observed phenomenon and the classical light, shape, and matter decomposition, we can take the example of a highlight. Its observed shape (by a human user or a sensor) is the resulting process of the interaction of these three components, and can be simulated this way. However, this does not provide any intuitive understanding of their relative influence on the final shape: an artist will directly describe the resulting shape, and not each of the three properties. We thus want to decompose the observed signal into models for each scale that can be easily understandable, representable, and manipulable. For this purpose, we will rely on the analysis of the resulting interaction of light, shape, and matter as observed by a human or a physical sensor. We first consider this analysis from an optical point of view, trying to identify the different phenomena and their scale according to their mathematical properties (e.g., differential  80 and frequency analysis  48). Such an approach has leaded us to exhibit the influence of surfaces flows (depth and normal gradients) into lighting pattern deformation (see Figure 4). For a human observer, this correspond to one recent trend in computer graphics that takes into account the human visual systems  49 both to evaluate the results and to guide the simulations.

3.4 Axis 2: From Acquisition to Display

Challenge: Convergence of optical and digital systems to blend real and virtual worlds.

Results: Instruments to acquire real world, to display virtual world, and to make both of them interact.

Figure 5.a
Figure 5.b

Light-Field transfer

Figure5: Light-Field transfer: global illumination between real and synthetic objects  41

In this axis, we investigate unified acquisition and display systems, that is systems which combine optical instruments with digital processing. From digital to real, we investigate new display approaches  69, 57. We consider projecting systems and surfaces  37, for personal use, virtual reality and augmented reality  32. From the real world to the digital world, we favor direct measurements of parameters for models and representations, using (new) optical systems unless digitization is required  51, 50. These resulting systems have to acquire the different phenomena described in Axis 1 and to display them, in an efficient manner  55, 31, 56, 59. By efficient, we mean that we want to shorten the path between the real world and the virtual world by increasing the data bandwidth between the real (analog) and the virtual (digital) worlds, and by reducing the latency for real-time interactions (we have to prevent unnecessary conversions, and to reduce processing time). To reach this goal, the systems have to be designed as a whole, not by a simple concatenation of optical systems and digital processes, nor by considering each component independently  60.

To increase data bandwidth, one solution is to parallelize more and more the physical systems. One possible solution is to multiply the number of simultaneous acquisitions (e.g., simultaneous images from multiple viewpoints  59, 78). Similarly, increasing the number of viewpoints is a way toward the creation of full 3D displays  69. However, full acquisition or display of 3D real environments theoretically requires a continuous field of viewpoints, leading to huge data size. Despite the current belief that the increase of computational power will fill the missing gap, when it comes to visual or physical realism, if you double the processing power, people may want four times more accuracy, thus increasing data size as well. To reach the best performances, a trade-off has to be found between the amount of data required to represent accurately the reality and the amount of required processing. This trade-off may be achieved using compressive sensing. Compressive sensing is a new trend issued from the applied mathematics community that provides tools to accurately reconstruct a signal from a small set of measurements assuming that it is sparse in a transform domain (e.g., 77, 102).

We prefer to achieve this goal by avoiding as much as possible the classical approach where acquisition is followed by a fitting step: this requires in general a large amount of measurements and the fitting itself may consume consequently too much memory and preprocessing time. By preventing unnecessary conversion through fitting techniques, such an approach increase the speed and reduce the data transfer for acquisition but also for display. One of the best recent examples is the work of Cossairt et al.  41. The whole system is designed around a unique representation of the energy-field issued from (or leaving) a 3D object, either virtual or real: the Light-Field. A Light-Field encodes the light emitted in any direction from any position on an object. It is acquired thanks to a lens-array that leads to the capture of, and projection from, multiple simultaneous viewpoints. A unique representation is used for all the steps of this system. Lens-arrays, parallax barriers, and coded-aperture  67 are one of the key technologies to develop such acquisition (e.g., Light-Field camera 1  60 and acquisition of light-sources  51), projection systems (e.g., auto-stereoscopic displays). Such an approach is versatile and may be applied to improve classical optical instruments  65. More generally, by designing unified optical and digital systems  74, it is possible to leverage the requirement of processing power, the memory footprint, and the cost of optical instruments.

Those are only some examples of what we investigate. We also consider the following approaches to develop new unified systems. First, similar to (and based on) the analysis goal of Axis 1, we have to take into account as much as possible the characteristics of the measurement setup. For instance, when fitting cannot be avoided, integrating them may improve both the processing efficiency and accuracy  76. Second, we have to integrate signals from multiple sensors (such as GPS, accelerometer, ...) to prevent some computation (e.g., 68). Finally, the experience of the group in surface modeling help the design of optical surfaces  63 for light sources or head-mounted displays.

3.5 Axis 3: Rendering, Visualization and Illustration

Challenge: How to offer the most legible signal to the final observer in real-time?

Results: High-level shading primitives, expressive rendering techniques for object depiction, real-time realistic rendering algorithms

Rendering techniques from realistic solutions to more expressive ones.

Figure6: In the MANAO project, we are investigating rendering techniques from realistic solutions (e.g., inter-reflections (a) and shadows (b)) to more expressive ones (shape enhancement (c) with realistic style and shape depiction (d) with stylized style) for visualization.

The main goal of this axis is to offer to the final observer, in this case mostly a human user, the most legible signal in real-time. Thanks to the analysis and to the decomposition in different phenomena resulting from interactions between light, shape, and matter (Axis 1), and their perception, we can use them to convey essential information in the most pertinent way. Here, the word pertinent can take various forms depending on the application.

In the context of scientific illustration and visualization, we are primarily interested in tools to convey shape or material characteristics of objects in animated 3D scenes. Expressive rendering techniques (see Figure 6c,d) provide means for users to depict such features with their own style. To introduce our approach, we detail it from a shape-depiction point of view, domain where we have acquired a recognized expertise. Prior work in this area mostly focused on stylization primitives to achieve line-based rendering  100, 64 or stylized shading  35, 98 with various levels of abstraction. A clear representation of important 3D object features remains a major challenge for better shape depiction, stylization and abstraction purposes. Most existing representations provide only local properties (e.g., curvature), and thus lack characterization of broader shape features. To overcome this limitation, we are developing higher level descriptions of shape  29 with increased robustness to sparsity, noise, and outliers. This is achieved in close collaboration with Axis 1 by the use of higher-order local fitting methods, multi-scale analysis, and global regularization techniques. In order not to neglect the observer and the material characteristics of the objects, we couple this approach with an analysis of the appearance model. To our knowledge, this is an approach which has not been considered yet. This research direction is at the heart of the MANAO project, and has a strong connection with the analysis we plan to conduct in Axis 1. Material characteristics are always considered at the light ray level, but an understanding of higher-level primitives (like the shape of highlights and their motion) would help us to produce more legible renderings and permit novel stylizations; for instance, there is no method that is today able to create stylized renderings that follow the motion of highlights or shadows. We also believe such tools also play a fundamental role for geometry processing purposes (such as shape matching, reassembly, simplification), as well as for editing purposes as discussed in Axis 4.

In the context of real-time photo-realistic rendering ((see Figure 6a,b), the challenge is to compute the most plausible images with minimal effort. During the last decade, a lot of work has been devoted to design approximate but real-time rendering algorithms of complex lighting phenomena such as soft-shadows  101, motion blur  48, depth of field  89, reflexions, refractions, and inter-reflexions. For most of these effects it becomes harder to discover fundamentally new and faster methods. On the other hand, we believe that significant speedup can still be achieved through more clever use of massively parallel architectures of the current and upcoming hardware, and/or through more clever tuning of the current algorithms. In particular, regarding the second aspect, we remark that most of the proposed algorithms depend on several parameters which can be used to trade the speed over the quality. Significant speed-up could thus be achieved by identifying effects that would be masked or facilitated and thus devote appropriate computational resources to the rendering  66, 47. Indeed, the algorithm parameters controlling the quality vs speed are numerous without a direct mapping between their values and their effect. Moreover, their ideal values vary over space and time, and to be effective such an auto-tuning mechanism has to be extremely fast such that its cost is largely compensated by its gain. We believe that our various work on the analysis of the appearance such as in Axis 1 could be beneficial for such purpose too.

Realistic and real-time rendering is closely related to Axis 2: real-time rendering is a requirement to close the loop between real world and digital world. We have to thus develop algorithms and rendering primitives that allow the integration of the acquired data into real-time techniques. We have also to take care of that these real-time techniques have to work with new display systems. For instance, stereo, and more generally multi-view displays are based on the multiplication of simultaneous images. Brute force solutions consist in independent rendering pipeline for each viewpoint. A more energy-efficient solution would take advantages of the computation parts that may be factorized. Another example is the rendering techniques based on image processing, such as our work on augmented reality  39. Independent image processing for each viewpoint may disturb the feeling of depth by introducing inconsistent information in each images. Finally, more dedicated displays  57 would require new rendering pipelines.

3.6 Axis 4: Editing and Modeling

Challenge: Editing and modeling appearance using drawing- or sculpting-like tools through high level representations.

Results: High-level primitives and hybrid representations for appearance and shape.

During the last decade, the domain of computer graphics has exhibited tremendous improvements in image quality, both for 2D applications and 3D engines. This is mainly due to the availability of an ever increasing amount of shape details, and sophisticated appearance effects including complex lighting environments. Unfortunately, with such a growth in visual richness, even so-called vectorial representations (e.g., subdivision surfaces, Bézier curves, gradient meshes, etc.) become very dense and unmanageable for the end user who has to deal with a huge mass of control points, color labels, and other parameters. This is becoming a major challenge, with a necessity for novel representations. This Axis is thus complementary of Axis 3: the focus is the development of primitives that are easy to use for modeling and editing.

More specifically, we plan to investigate vectorial representations that would be amenable to the production of rich shapes with a minimal set of primitives and/or parameters. To this end we plan to build upon our insights on dynamic local reconstruction techniques and implicit surfaces  4034. When working in 3D, an interesting approach to produce detailed shapes is by means of procedural geometry generation. For instance, many natural phenomena like waves or clouds may be modeled using a combination of procedural functions. Turning such functions into triangle meshes (main rendering primitives of GPUs) is a tedious process that appears not to be necessary with an adapted vectorial shape representation where one could directly turn procedural functions into implicit geometric primitives. Since we want to prevent unnecessary conversions in the whole pipeline (here, between modeling and rendering steps), we will also consider hybrid representations mixing meshes and implicit representations. Such research has thus to be conducted while considering the associated editing tools as well as performance issues. It is indeed important to keep real-time performance (cf. Axis 2) throughout the interaction loop, from user inputs to display, via editing and rendering operations. Finally, it would be interesting to add semantic information into 2D or 3D geometric representations. Semantic geometry appears to be particularly useful for many applications such as the design of more efficient manipulation and animation tools, for automatic simplification and abstraction, or even for automatic indexing and searching. This constitutes a complementary but longer term research direction.

A system that mimics texture (left) and shading (right) effects using image processing alone.

Figure7: Based on our analysis  97 (Axis 1), we have designed a system that mimics texture (left) and shading (right) effects using image processing alone. It takes depth (a) and normal (d) images as input, and uses them to deform images (b-e) in ways that closely approximate surface flows (c-f). It provides a convincing, yet artistically controllable illusion of 3D shape conveyed through texture or shading cues.

In the MANAO project, we want to investigate representations beyond the classical light, shape, and matter decomposition. We thus want to directly control the appearance of objects both in 2D and 3D applications (e.g., 94): this is a core topic of computer graphics. When working with 2D vector graphics, digital artists must carefully set up color gradients and textures: examples range from the creation of 2D logos to the photo-realistic imitation of object materials. Classic vector primitives quickly become impractical for creating illusions of complex materials and illuminations, and as a result an increasing amount of time and skill is required. This is only for still images. For animations, vector graphics are only used to create legible appearances composed of simple lines and color gradients. There is thus a need for more complex primitives that are able to accommodate complex reflection or texture patterns, while keeping the ease of use of vector graphics. For instance, instead of drawing color gradients directly, it is more advantageous to draw flow lines that represent local surface concavities and convexities. Going through such an intermediate structure then allows to deform simple material gradients and textures in a coherent way (see Figure 7), and animate them all at once. The manipulation of 3D object materials also raises important issues. Most existing material models are tailored to faithfully reproduce physical behaviors, not to be easily controllable by artists. Therefore artists learn to tweak model parameters to satisfy the needs of a particular shading appearance, which can quickly become cumbersome as the complexity of a 3D scene increases. We believe that an alternative approach is required, whereby material appearance of an object in a typical lighting environment is directly input (e.g., painted or drawn), and adapted to match a plausible material behavior. This way, artists will be able to create their own appearance (e.g., by using our shading primitives  94), and replicate it to novel illumination environments and 3D models. For this purpose, we will rely on the decompositions and tools issued from Axis 1.

4 Application domains

4.1 Physical Systems

Given our close relationships with researchers in optics, one novelty of our approach is to extend the range of possible observers to physical sensors in order to work on domains such as simulation, mixed reality, and testing. Capturing, processing, and visualizing complex data is now more and more accessible to everyone, leading to the possible convergence of real and virtual worlds through visual signals. This signal is traditionally captured by cameras. It is now possible to augment them by projecting (e.g., the infrared laser of Microsoft Kinect) and capturing (e.g., GPS localization) other signals that are outside the visible range. This supplemental information replaces values traditionally extracted from standard images and thus lowers down requirements in computational power. Since the captured images are the result of the interactions between light, shape, and matter, the approaches and the improved knowledge from MANAO help in designing interactive acquisition and rendering technologies that are required to merge the real and the virtual worlds. With the resulting unified systems (optical and digital), transfer of pertinent information is favored and inefficient conversion is likely avoided, leading to new uses in interactive computer graphics applications, like augmented reality, displays and computational photography.

4.2 Interactive Visualization and Modeling

This direction includes domains such as scientific illustration and visualization, artistic or plausible rendering, and 3D modeling. In all these cases, the observer, a human, takes part in the process, justifying once more our focus on real-time methods. When targeting average users, characteristics as well as limitations of the human visual system should be taken into account: in particular, it is known that some configurations of light, shape, and matter have masking and facilitation effects on visual perception. For specialized applications (such as archeology), the expertise of the final user and the constraints for 3D user interfaces lead to new uses and dedicated solutions for models and algorithms.

5 Social and environmental responsibility

5.1 Footprint of research activities

For a few years now, our team has been collectively careful in limiting its direct environmental impacts, mainly by limiting the number of flights and extending the lifetime of PCs and laptops beyond the warranty period.

5.2 Environmental involvement

Gaël Guennebaud and Pascal Barla are engaged in several actions and initiatives related to the environmental issues, both within Inria itself, and within the research and higher-education domain in general:

  • They have been members of the “Local Sustainable Development Committee” of Inria Bordeaux until November 2023.
  • They are animators of the “The Climate Fresk”.
  • G. Guennebaud is a member of the “Social and Environmental Responsibility Committee” of the LaBRI and of the “transition network” of the University of Bordeaux.
  • Ecoinfo: G. Guennebaud is involved within the GDS Ecoinfo of the CNRS, and in particular he is in charge of the development of the ecodiag tool among other activities.
  • Labo1point5: G. Guennebaud is part of the labos1point5 GDR, in particular to help with the development of a module to take into account the carbon footprint of ICT devices within their carbon footprint estimation tool (GES1point5). The first version of the module has been released in October 2021.
  • G. Guennebaud participate in the elaboration and dissemination of an introductory course to climate change issues and environnemental impacts of ICT, with two colleagues of the LaBRI.
  • P. Barla and G. Guennebaud have compiled research projects conducted by Inria teams around environmental issues within Bordeaux research center, and prepared material for presentation to different audiences.

6 Highlights of the year

A publication in the presitigious “Natural Human Behaviour” journal 11, on the perception of material categories from specular image features, in collaboration with researchers in Psychophysics at the University of Giessen, Germany.

7 New software, platforms, open data

7.1 New software

7.1.1 Spectral Viewer

  • Keyword:
  • Functional Description:
    An open-source (spectral) image viewer that supports several images formats: ENVI (spectral), exr, png, jpg.
  • URL:
  • Authors:
    Arthur Dufay, Romain Pacanowski, Pascal Barla, Alban Fichet, David Murray
  • Contact:
    Romain Pacanowski
  • Partner:
    LP2N (CNRS - UMR 5298)

7.1.2 Malia

  • Name:
    The Malia Rendering Framework
  • Keywords:
    3D, Realistic rendering, GPU, Ray-tracing, Material appearance
  • Functional Description:
    The Malia Rendering Framework is an open source library for predictive, physically-realistic rendering. It comes with several applications, including a spectral path tracer, RGB-to-spectral conversion routines a blender bridge and a spectral image viewer.
  • URL:
  • Authors:
    Arthur Dufay, Romain Pacanowski, Pascal Barla, David Murray, Alban Fichet
  • Contact:
    Romain Pacanowski

7.1.3 FRITE

  • Keywords:
    2D animation, Vector-based drawing
  • Functional Description:
    2D animation software allowing non linear editing
  • Authors:
    Pierre Benard, Pascal Barla
  • Contact:
    Pierre Benard

7.1.4 ecodiag

  • Keywords:
    CO2, Carbon footprint, Web Services
  • Functional Description:
    Ecodiag is a web service to estimate the carbon footprint of the computer equipments.
  • Contact:
    Gael Guennebaud
  • Partner:

7.1.5 FtthPowerSim

  • Keywords:
    Power consumption, Network simulator
  • Functional Description:
    This web application is a demo of the methodology and model detailed in the paper Assessing VoD pressure on network power consumption. It's purpose is to estimate the dimensioning and power consumption of a fiber network infrastructure that is ideally sized to satisfy different usage scenarios. It is tailored to cover a territory of the size of France centered around a main IXP collocated with a unique CDN playing the role of a cache.
  • URL:
  • Contact:
    Gael Guennebaud
  • Partners:
    Université de Bordeaux, LaBRI

7.2 New platforms

7.2.1 La Coupole

Participants: Romain Pacanowski, Marjorie Paillet, Morgane Gerardin, David Murray.

Figure 8.a
Figure 8.b

View of La Coupole


Left, view of La Coupole and the robot with the 3D scanner mounted, before the acquisition phase of the optical properties performed with a high speed camera (Right) that photographs the object for each lit LED. (Photo Credits Arthur Pequin.)

La Coupole is a measurement device that acquires spatially-varying reflectance function (SV-BRDF) on non-planar object which area can be up to 1.5m2.

Its main characteristics are:

  • RGB 12MP Camera (100 fps)
  • 6-axes Robot
  • 1080 White LED
  • 3D Laser Scanner Laser: 200 μm resolution
  • Maximal Measurement Area: 1.75 m2
  • Optical Resolution: 50 μm

Left, official poster of the Exhibition Textiles 3D presented to the museum of Ethnography of Bordeaux. Center and Right, 3D digital reconstruction of an alabaster piece using data acquired by La Coupole.

Official poster of the Exhibition and 3D digital reconstruction of an alabaster.


Left, official poster of the Exhibition Textiles 3D presented to the museum of Ethnography of Bordeaux. Center and Right, 3D digital reconstruction of an alabaster piece using data acquired by La Coupole.

La Coupole is capable of measuring objects with an average angular accuracy of 0.22 degrees, generates 4 terabytes of data per hour of measurement and allows the measurement of spatially varying BRDFs (SV-BRDF) on a non-planar shape. The 50 mm lens combined with the camera allows to obtain a spatial resolution resolution of 50 microns which corresponds approximately to the resolution of the human visual system (for an object placed at about 20 cm from the observer). After two years of conception and realization, la Coupole was used to digitize 10 garments from the collections (cf. Figure 10) of the Ethnography Museum of Bordeaux as well as as well as a reconstruction of an alabaster (cf. Figure 9) within the framework of the project LaBeX "Albâtres" project and will continue to be used the project VESPAA.

Examples of numerical reconstructions from data acquired with La Coupole.


Numerical reconstructions with albedo (hemispherical reflectivity) per mesh vertex for different types of clothing : Left, the woman's silk and cotton vest (Tibet, late nineteenth century), a video featuring other points of view viewpoints is available here. Center,partial view of a central ornament of the apron: in navy blue quilted satin with embroidery in net representing a lion's head, and blue, white and red floche silk embroideries, a little yellow; black velvet facings; origin: China, 19th century. Right, coat made of fish skins from Siberia (twentieth century), a video showing other views is available views is availablehere.

7.2.2 Measuring Bidirectional Subscattering Reflectance and Transmission Functions

Participants: Morgane Gerardin, Romain Pacanowski.

A new platform (cf. Figure 11) to measure the volumetric properties of the light is currently being developed. The project started in March 2022 with the arrival of our new postdoctoral fellow Morgane Gérardin. The plaform permits to measure the diffusion of the light in reflection (aka BSSRDF) but also in Transmission (BSSTDF). A sample holder with two motorized axes orientates the sample wrt. to the direction of incident illumination while another motorized axis rotates a camera to image the sample (cf. Figure 12).

The BSSxDF measurement platform.

Figure11: The BSSxDF measurement platform. Left: Optical setup to collimate a K5600 Joker light to a 1mm2 spot on the material sample. Center: Sample holder; here alabaster. Right: Incident illumination at 550nm wavelength focused on the material sample, revealing lateral light transport.
Figure 12

Measurement principle

Figure12: Measurement principle: a DSLR camera takes picture all around the material sample. Here shown with a Charucco calibration target used to calibrate the camera intrinsics and extrinsics parameters.

8 New results

8.1 Analysis and Simulation

8.1.1 Material category of visual objects computed from specular image structure

Participants: Alexandra Schmidt [Univerity of Giessen], Pascal Barla, Katja Doerschner [Univerity of Giessen].

Recognizing materials and their properties visually is vital for successful interactions with our environment, from avoiding slippery floors to handling fragile objects. Yet there is no simple mapping of retinal image intensities to physical properties. In this paper 11, we investigated what image information drives material perception by collecting human psychophysical judgements about complex glossy objects (Figure 13). Variations in specular image structure—produced either by manipulating reflectance properties or visual features directly—caused categorical shifts in material appearance, suggesting that specular reflections provide diagnostic information about a wide range of material classes. Perceived material category appeared to mediate cues for surface gloss, providing evidence against a purely feedforward view of neural processing. Our results suggest that the image structure that triggers our perception of surface gloss plays a direct role in visual categorization, and that the perception and neural processing of stimulus properties should be studied in the context of recognition, not in isolation.

Figure 13

Dragon shape with (left) a 'melted chocolate' or 'mud' appearance; (center) a 'latex' or 'rubber' appearance; (right) a 'velvet', 'silk' or 'fabric' appearance.

Figure13: Multiple semantic terms can describe the same qualitative visual appearance of a material. The object in the first panel has a dark brown, lumpy surface with medium-clarity specular reflections and could be labelled 'melted chocolate' or 'mud'. This surface has a different visual quality from the object in the middle panel, which has low-clarity, dim reflections that make it look like 'latex' or 'rubber'. The object in the third panel has very rough, anisotropic specular reflections that rapidly change in brightness at the boundaries between highlights and lowlights, giving it the visual characteristics of 'velvet', 'silk' or 'fabric'.

8.2 From Acquisition to Display

8.2.1 Depth from Focus using Windowed Linear Least Squares Regressions

Participants: Corentin Cou, Gaël Guennebaud.

We present in this paper 9 a novel depth from focus technique. Following prior work, our pipeline starts with a focal stack and an estimation of the amount of defocus as given by, for instance, the Ring Difference Filter. To improve robustness to outliers while avoiding to rely on costly non-linear optimizations, we propose an original scheme that linearly scans the profile over a fixed size window, searching for the best peak within each window using a linearized least-squares Laplace regression. As a post-process, depth estimates with low confidence are reconstructed though an adaptive Moving Least Squares filter. We show how to objectively evaluate the performance of our approach by generating synthetic focal stacks from which the reconstructed depth maps can be compared to ground truth (Figure 14). Our results show that our method achieves higher accuracy than previous non-linear Laplace regression technique, while being orders of magnitude faster.

Figure 14

Depth from focus acquisition setup and results

Figure14: Left: Acquisition setup. Right: Results on a real-word stack from an engraved stone. Top: 3D profile of the acquired engraving area. Bottom left: blurry image obtained on the image stack. Bottom right: reconstituted clear image of the engraving.

8.3 Rendering, Visualization and Illustration

8.3.1 A Micrograin BSDF Model for the Rendering of Porous Layers

Participants: Simon Lucas, Mickaël Ribardière [Université de Poitiers], Romain Pacanowski, Pascal Barla.

We introduce a new BSDF model for the rendering of porous layers, as found on surfaces covered by dust, rust, dirt, or sprayed paint (Figure 15). Our approach 16 is based on a distribution of elliptical opaque micrograins, extending the Trowbridge-Reitz (GGX) distribution to handle pores (i.e., spaces between micrograins). We use distance field statistics to derive the corresponding Normal Distribution Function (NDF) and Geometric Attenuation Factor (GAF), as well as a view- and light- dependent filling factor to blend between the porous and base layers. All the derived terms show excellent agreement when compared against numerical simulations. Our approach has several advantages compared to previous work. First, it decouples structural and reflectance parameters, leading to an analytical single-scattering formula regardless of the choice of micrograin reflectance. Second, we show that the classical texture maps (albedo, roughness, etc) used for spatially-varying material parameters are easily retargeted to work with our model. Finally, the BRDF parameters of our model behave linearly, granting direct multi-scale rendering using classical mip mapping.

Figure 15

Micrograin BSDF model

Figure15: Our micrograin BSDF model provides a physically-plausible solution for laying porous layers onto an arbitrary surfaces. This is here shown for a number of materials: we use diffuse grains on a plastic watering can to reproduce mud, copper oxide grains on a metallic bucket for rust, diffuse grains on a transparent glass for dirt, gold grains on diffuse or aluminium vases to mimic spray paint, soot grains on the diffuse broken pots and diffuse grains on wooden shelves.

8.4 Editing and Modeling

8.4.1 Non-linear Rough 2D Animation using Transient Embeddings

Participants: Melvin Even, Pierre Bénard, Pascal Barla.

Traditional 2D animation requires time and dedication since tens of thousands of frames need to be drawn by hand for a typical production. Many computer-assisted methods have been proposed to automatize the generation of inbetween frames from a set of clean line drawings, but they are all limited by a rigid workflow and a lack of artistic controls, which is in the most part due to the one-to-one stroke matching and interpolation problems they attempt to solve. In this work 10, we take a novel view on those problems by focusing on an earlier phase of the animation process that uses rough drawings (i.e., sketches). Our key idea is to recast the matching and interpolation problems so that they apply to transient embeddings, which are groups of strokes that only exist for a few keyframes. A transient embedding carries strokes between keyframes both forward and backward in time through a sequence of transformed lattices. Forward and backward strokes are then cross-faded using their thickness to yield rough inbetweens. With our approach, complex topological changes may be introduced while preserving visual motion continuity. As demonstrated on state-of-the-art 2D animation exercises (e.g., Figure 16), our system provides unprecedented artistic control through the non-linear exploration of movements and dynamics in real-time.

Figure 16

Flame animation produced with our rough 2D animation system

Figure16: Our rough animation system supports the inbetweening of complex special effects with multiple topological events, here a flame splitting into smaller components. In (a), we show the input key drawings traced over a reference from Gilland's book, while in (b) we show their decomposition into transient embeddings. Even though we use a unique color per embedding throughout the animation for visualization, each embedding only exists between a pair of keyframes in this example. This allows the handling of topological changes, which occur at the third and fifth keyframes. In (c), we display in magenta a subset of the inbetween frames generated by our animation system in real-time.

8.4.2 Efficient Interpolation of Rough Line Drawings

Participants: Jiazhou Chen [Zhejiang University of Technology], Xinding Zhu [Zhejiang University of Technology], Melvin Even, Jean Basset, Pierre Bénard, Pascal Barla.

In traditional 2D animation, sketches drawn at distant keyframes are used to design motion, yet it would be far too labor-intensive to draw all the inbetween frames to fully visualize that motion. We propose a novel efficient interpolation algorithm that generates these intermediate frames in the artist's drawing style 8. Starting from a set of registered rough vector drawings, we first generate a large number of candidate strokes during a pre-process, and then, at each intermediate frame, we select the subset of those that appropriately conveys the underlying interpolated motion, interpolates the stroke distributions of the key drawings, and introduces a minimum amount of temporal artifacts (Figure 17). In addition, we propose quantitative error metrics to objectively evaluate different stroke selection strategies. We demonstrate the potential of our method on various animations and drawing styles, and show its superiority over competing raster- and vector-based methods.

Figure 17

Rough drawing animation of a bear

Figure17: Our interpolation technique takes as input a series of rough vector key drawings (shown in light gray), and produces intermediate drawings (in black) that preserve the input drawing style(s). It is based on an interactive stroke distribution synthesis algorithm that introduces a minimum amount of temporal artifacts.

8.4.3 One-to-Many Spectral Upsampling of Reflectances and Transmittances

Participants: Laurent Belcour [Unity Labs, Grenoble], Pascal Barla.

Spectral rendering is essential for the production of physically-plausible synthetic images, but requires to introduce several changes in the content generation pipeline. In particular, the authoring of spectral material properties (e.g., albedo maps, indices of refraction, transmittance coefficients) raises new problems. While a large panel of computer graphics methods exists to upsample a RGB color to a spectrum, they all provide a one-to-one mapping. This limits the ability to control interesting color changes such as the Usambara effect or metameric spectra (Figure 18). In this work 7, we introduce a one-to-many mapping in which we show how we can explore the set of all spectra reproducing a given input color. We apply this method to different colour changing effects such as vathochromism - the change of color with depth, and metamerism.

Figure 18

Usambara effect

Figure18: Surprising color changes may occur due to the path length travelled by light through some materials. This is shown in (a) with the Usambara effect observed in tourmaline: the same gem appears green or red depending on path length, due to a specific transmission spectrum (see inset). We introduce a method for finding such non-generic spectra. This requires to perform one-to-many spectral upsampling (b), which generates multiple spectra with a unique controllable color at a given path length, but varying colors at further lengths. The chromaticity of each spectrum as a function of path lengths is shown in (c).

8.4.4 FlavoMetrics: Towards a Digital Tool to Understand and Tune Living Aesthetics of Flavobacteria

Participants: Clarice Risseeuw [Technical University, Delft], Jose Castro [Technical University, Delft], Pascal Barla, Elvin Karana [Technical University, Delft].

Integrating microorganisms into artefacts is a growing area of interest for HCI designers. However, the time, resources, and knowledge required to understand complex microbial behaviour limits designers from creatively exploring temporal expressions in living artefacts, i.e., living aesthetics. Bridging biodesign and computer graphics, we developed FlavoMetrics 17, an interactive digital tool that supports biodesigners in exploring Flavobacteria's living aesthetics (Figure 19). This open-source tool enables designers to virtually inoculate bacteria and manipulate stimuli to tune Flavobacteria's living colour in a digital environment. Six biodesigners evaluated the tool and reflected on its implications for their practices, for example, in (1) understanding spatio-temporal qualities of microorganisms beyond 2D, (2) biodesign education, and (3) the experience prototyping of living artefacts. With FlavoMetrics, we hope to inspire novel HCI tools for accessible and time- and resource-efficient biodesign as well as for better alignment with divergent microbial temporalities in living with living artefacts.

Figure 19


Figure19: Left: Real photograph of Flavobacteria; Right: Screen capture of FlavoMetrics, our interactive digital tool that supports biodesigners in exploring Flavobacteria's living aesthetics.

8.4.5 ImmersiveIML - Immersive interactive machine learning for 3D point cloud classification

Participants: Maxime Cordeil [University of Queensland], Thomas Billy [University of Queensland], Nicolas Mellado [CNRS, IRIT, Universite de Toulouse], Loïc Barthe [CNRS, IRIT, Universite de Toulouse], Nadine Couture [Univ. Bordeaux, ESTIA Institute of Technology], Patrick Reuter.

We propose in this work 14 an initial exploration of an interactive machine learning (IML) dialogue in immersive, interactive Virtual Reality (VR) for the classification of points in 3D point clouds. We contribute ImmersiveIML, an Immersive Analytics tool which builds on humanmachine learning trial-and-error dialogue to support an iterative classification process of points in the 3D point cloud. The interactions in ImmersiveIML are designed to be both expressive and minimal; we designed the iterative process to be supported by (1) 6-DOF controllers to allow direct interaction in large 3D point clouds via a minimal brushing technique, (2) a fast trainable machine learning model, and (3) the direct visual feedback of classification results.

This constitutes an iterative human-in-the-loop process that eventually converges to a classification according to human intent. We argue that this approach is a novel contribution that supports a constant improvement of the classification model and fast tracks classification tasks with this type of data, in an immersive scenario. We report on the design and implementation of ImmersiveIML and demonstrate its capabilities with two emblematic application scenarios: edge detection in 3D and classification of trees in a city LiDAR dataset.

Figure 20

Iterative human-in-the-loop classification of points in 3D point clouds

Figure20: Starting from a human intent, the iterative human-in-the-loop process is composed of (1) 6-DOF controllers to allow direct interaction in large 3D point clouds via a minimal brushing technique, (2) a fast trainable machine learning model, and (3) the direct visual feedback of classification results. In the shown iteration, the classification result does not correspond to the user's intent, so they refine the input to eventually converge to an acceptable classification of the data, iteratively.

8.5 Modeling environnemental impacts of digitization

Participants: Gaël Guennebaud, Aurélie Bugeau [Université de Bordeaux, LaBRI].

Assessing the energy consumption or carbon footprint of data distribution of video streaming services is usually carried out through energy or carbon intensity figures (in Wh or gCO2e per GB). In a ICT4S paper 15 we reviewed the reasons why such approaches are likely to lead to misunderstandings and potentially to erroneous conclusions. To overcome those shortcomings, we designed a new methodology whose key idea is to consider a video streaming usage at the whole scale of a territory, and evaluate the impact of this usage on the network infrastructure. At the core of our methodology is a parametric model of a simplified network and Content Delivery Network (CDN) infrastructure, which is automatically scaled according to peak usage needs. This allows us to compare the power consumption of this infrastructure under different scenarios, ranging from a sober baseline to a generalized use of high bitrate videos. Our results show that classical efficiency indicators do not reflect the power consumption increase of more intensive Internet usage, and might even lead to misleading conclusions. This makes our approach more suitable to drive actions and study “What-if” scenarios. Our model is publicly available as a web application illustrated in Figure 21.

Figure 21

Parametric network model for streaming applications

Figure21: Illustration of our simplified parametric model of a network with estimated power consumption for different video qualities and baseline network settings.

9 Bilateral contracts and grants with industry

9.1 Bilateral contracts with industry

Research collaboration contract with Praxinos (2021-2024)

Participants: Melvin Even, Pierre Bénard, Pascal Barla.

This collaboration aims at defining new computer-assisted tools to facilitate the creation of 2D animations.


CIFRE PhD contract with Ubisoft (2022-2025)

Participants: Panagiotis Tsiapkolis, Pierre Bénard.

In this project, we aim at exploring artistic control in real-time stylized rendering of 3D scenes.

10 Partnerships and cooperations

10.1 International initiatives

10.1.1 Visits to international teams

Research stays abroad

Patrick Reuter

  • Visited institutions:
    Monash University (Department of Human-Centred Computing) and University of Queensland (Human-Centred Computing team)
  • Country:
  • Dates:
    September 2022 - August 2023
  • Context of the visit:
  • Type of mobility:
    research stay

The primary objective of this research stay is to foster collaborations and explore interactive machine learning approaches for geometry processing.

10.2 National initiatives

10.2.1 ANR

“Young Researcher” MoStyle (2021-2025)


Participants: Pierre Bénard, Pascal Barla, Melvin Even.

The main goal of this project is to investigate how computer tools can help capturing and reproducing the typicality of traditional 2D animations. Ultimately, this would allow to produce 2D animations with a unified appearance starting from roughs drawings or 3D inputs.

10.2.2 Inria Exploratory actions

Exploratory Action Ecoptics (2021-2024)


Participants: Gary Fourneau, Pascal Barla, Romain Pacanowski.

The main topic of this project is to contribute to the understanding of visual communication among animals. It explores new computer graphics techniques Il se propose de déveloper de nouvelles techniques de synthèse d'images afin de combler le fossé qui sépare les approches optique et écologique, connectant ainsi le transport lumineux dans des structures microscopiques à la surface d'un animal, aux signaux visuels perceptibles par un autre animal dans son habitat.

10.3 Regional initiatives

Vespaa (2022-2027)

 - INRIA and Region Nouvelle Aquitaine

Participants: Romain Pacanowski, Pierre Bénard, Pascal Barla, Gael Guennebaud, Pierre Mézière.

The project VESPAA focuses on high-fidelity rendering of African artifacts stored in different museums (Angoulême, La Rochelle, Bordeaux) of the Nouvelle Aquitaine Region.

The main goals of VESPAA are:

  • To improve the quality of measurements data acquired by La Coupole in order to represent complex materials (gilding, pearl, patina and varnish)
  • To develop new SV-BRDF models and multi-resolution representations to visualize in real-time and with high fidelity the digitized objects under dynamic light and view directions. The targeted audience ranges from Cultural Heritage experts to mainstream public visiting the museums.
  • To make durable the acquired reflectance properties by storing the measurements (geometry and tabulated data) as well as the SV-BRDF models (Source Code) in a open database.

11 Dissemination

11.1 Promoting scientific activities

  • ACM Siggraph, ACM Siggraph Asia
  • Eurographics
  • Eurographics Symposium on Rendering
  • ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games (i3D)
  • ACM Symposium on User Interface Software and Technology (UIST)

11.1.1 Journal

  • IEEE Transactions on Visualization and Computer Graphics
  • Journal of Industrial Ecology
  • IPOL

11.1.2 Invited talks

  • Appamat Workshop on Wet Materials (Pascal Barla).

11.1.3 Scientific expertise

  • Gaël Guennebaud is providing expertize within two working groups of TheShiftProject on sufficiency in future Internet mobile network and on the role and impact of technologies within low GHG emission and resilient agricultural scenarios.

11.2 Teaching - Supervision - Juries

11.2.1 Teaching

The members of our team are involved in teaching computer science at University of Bordeaux and ENSEIRB-Matmeca engineering School. General computer science is concerned, as well as the following graphics related topics:

  • Master: Pierre Bénard, Gaël Guennebaud, Romain Pacanowski, Advanced Image Synthesis, 50 HETD, M2, Univ. Bordeaux, France.
  • Master: Gaël Guennebaud, Pierre Bénard and Simon Lucas, 3D Worlds, 60 HETD, M1, Univ. Bordeaux and IOGS, France.
  • Master: Pierre Bénard, Virtual Reality, 20 HETD, M2, Univ. Bordeaux, France.
  • Master: Romain Pacanowski, 3D Programming, M2, 18 HETD, Bordeaux INP ENSEIRB Matmeca, France.
  • Licence: Gaël Guennebaud and Pierre La Rocca, Introduction to climate change issues and the environnemental impacts of ICT, 24 HETD, L3, Univ. Bordeaux, France.

One member is also in charge of a field of study:

  • Master: Pierre Bénard, M2 “Informatique pour l'Image et le Son”, Univ. Bordeaux, France.

11.2.2 Supervision

  • PhD: Corentin Cou, “Characterization of visual appearance for 3D restitution and exploration of monumental heritage”, Inria & IOGS & CNRS/INHA, G. Guennebaud, X. Granier, M. Volait, R. Pacanowski. 08/12/2024
  • PhD in progress: Melvin Even, “Computer-Aided Rough 2D Animation”, Inria & Univ. Bordeaux, P. Barla, P. Bénard
  • PhD in progress: Gary Fourneau, “ Modélisation de l'Apparence Visuelle pour l'Écologie Comportementale”, Inria & Univ. Bordeaux, P. Barla, R. Pacanowski
  • PhD in progress: Simon Lucas, “Modélisation de l'apparence et rendu des plantes”, Inria & Univ. Bordeaux, P. Barla, R. Pacanowski
  • PhD in progress: Panagiotis Tsiapkolis, “Study of Artistic Control in Real-Time Expressive Rendering”, Inria & Ubisoft, P. Bénard
  • PhD in progress: Pierre La Rocca, “Modélisation paramétrique des impacts environnementaux des TIC : focus sur la numérisation de l'agriculture.”, Univ. Bordeaux, Aurélie Bugeau, G. Guennebaud

11.2.3 Juries

Phd Thesis
  1. Fanny Dailliez (Université Grenoble Alpes): Multiscale impact of the addition of a coating layer on the color of halftone prints. PhD Defense Date: October 19th 2023. Jury:
    1. Carinna PARRAMAN, Reviewer (CFPR)
    2. Romain Pacanowski Reviewer (Inria)
    3. Clotilde BOUST, Examiner (C2RMF)
    4. Evelyne MAURET, Examiner (LGP2)
    5. Anne BLAYO, Director (LGP2)
    6. Lionel CHAGAS, Supervisor, (LGP2)
    7. Thierry FOURNEL, Co-director, (Lab. Hubert Curien)
    8. Mathieu HEBERT, Supervisor, (Lab. Hubert Curien)
  2. Vincent Duveiller (Université Jean Monnet, IOGS): Optical models for predicting the color of dental composite materials. PhD Defense Date: Jury:
    • GHINEA Razvan, Reviewer (University of Granada, Facultad de Ciencia)
    • PILLONNET Anne, Reviewer (Université Claude Bernard Lyon 1, ILM)
    • ANDRAUD Christine, Examiner (Muséum National d’Histoire Naturelle)
    • PACANOWSKI Romain, Examiner (Inria)
    • VYNCK Kevin, Examiner (CNRS)
    • HEBERT Mathieu, Director (Université Jean Monnet, IOGS)
    • CLERC Raphaël, Co-director (Université Jean Monnet, IOGS)
    • SALOMON Jean-Pierre, invited (Université de Lorraine, Faculté de Nancy)
    • JOST Sophie, invited (ENTPE)

11.3 Popularization

  • During the national “Semaine des maths” event at INRIA (06/03/2023), Pierre Bénard gave a 45 minutes talk titled L'art et la science des films d'animation 3D.

12 Scientific production

12.1 Major publications

  • 1 articleL.Laurent Belcour and P.Pascal Barla. A Practical Extension to Microfacet Theory for the Modeling of Varying Iridescence.ACM Transactions on Graphics364July 2017, 65HALDOI
  • 2 articleT.Thomas Crespel, P.Patrick Reuter, A.Adrian Travis, Y.Yves Gentet and X.Xavier Granier. Autostereoscopic transparent display using a wedge light guide and a holographic optical element: implementation and results.Applied optics5834November 2019HALDOI
  • 3 articleN.Nicolas Holzschuch and R.Romain Pacanowski. A Two-Scale Microfacet Reflectance Model Combining Reflection and Diffraction.ACM Transactions on Graphics364Article 66July 2017, 12HALDOI
  • 4 articleT.Thibaud Lambert, P.Pierre Bénard and G.Gaël Guennebaud. A View-Dependent Metric for Patch-Based LOD Generation & Selection.Proceedings of the ACM on Computer Graphics and Interactive Techniques11May 2018HALDOI
  • 5 articleG.Georges Nader and G.Gaël Guennebaud. Instant Transport Maps on 2D Grids.ACM Transactions on Graphics376November 2018, 13HALDOI
  • 6 articleA.Alexandra Schmid, P.Pascal Barla and K.Katja Doerschner. Material category of visual objects computed from specular image structure.Nature Human Behaviour77July 2023, 1152-1169HALDOI

12.2 Publications of the year

International journals

International peer-reviewed conferences

Conferences without proceedings

  • 18 inproceedingsA.Adrian Agreda, T.Tong Wu, A.Adrian Hereu, R.Romain Pacanowski, A.Arthur Dufay, X.Xavier Granier, M.Mona Tréguer-Delapierre, G. L.Glenna L Drisko, K.Kevin Vynck and P.Philippe Lalanne. Control of visual appearance with disordered plasmonic resonant metasurfaces.SPP 2023 - The International Conference on Surface Plasmon Photonics 10Houston, TX,, FranceMay 2023HAL
  • 19 inproceedingsC.Corentin Cou, H.Hortense de La Codre, X.Xavier Granier and A.Aurélie Mounier. Pearson correlation-based method on hyperspectral images for the study of similarity of pigments and dyes.International conference on analytical techniques in art and cultural heritage - TECHNART 2023 LISBONLisbonne, PortugalMay 2023HAL
  • 20 inproceedingsC.Corentin Cou, R.Romain Pacanowski and X.Xavier Granier. In-situ and highly portable SVBRDF acquisition method.IS&T/Appamat International Workshop on Material AppearanceParis, FranceNovember 2023HAL

Scientific book chapters

Doctoral dissertations and habilitation theses

  • 22 thesisC.Corentin Cou. New approach of 3D for monumental heritage.Université de BordeauxDecember 2023HAL
  • 23 thesisR.Romain Pacanowski. Toward a complete predictive rendering pipeline for numerical prototyping and cultural heritage applications.Université de Bordeaux (UB)June 2023HAL

Reports & preprints

12.3 Other


12.4 Cited publications

  • 28 articleM.Marc Alexa and W.Wojciech Matusik. Reliefs as images.ACM Trans. Graph.2942010, URL: http://doi.acm.org/10.1145/1778765.1778797DOIback to text
  • 29 articleL.Lucas Ammann, P.Pascal Barla, X.Xavier Granier, G.Gaël Guennebaud and P.Patrick Reuter. Surface Relief Analysis for Illustrative Shading.Computer Graphics Forum314June 2012, 1481-1490URL: http://hal.inria.fr/hal-00709492DOIback to textback to text
  • 30 techreportM.Michael Ashikhmin and S.Simon Premoze. Distribution-based BRDFs.unpublishedUniv. of Utah2007back to text
  • 31 articleB.Brad Atcheson, I.Ivo Ihrke, W.Wolfgang Heidrich, A.Art Tevs, D.Derek Bradley, M.Marcus Magnor and H.-P.Hans-Peter Seidel. Time-resolved 3D Capture of Non-stationary Gas Flows.ACM Trans. Graph.2752008back to text
  • 32 bookO.Oliver Bimber and R.Ramesh Raskar. Spatial Augmented Reality: Merging Real and Virtual Worlds.A K Peters/CRC Press2005back to textback to text
  • 33 articleA.Adrien Bousseau, E.Emmanuelle Chapoulie, R.Ravi Ramamoorthi and M.Maneesh Agrawala. Optimizing Environment Maps for Material Depiction.Comput. Graph. Forum (Proceedings of the Eurographics Symposium on Rendering)3042011, URL: http://www-sop.inria.fr/reves/Basilic/2011/BCRA11back to text
  • 34 articleS.Simon Boyé, G.Gaël Guennebaud and C.Christophe Schlick. Least Squares Subdivision Surfaces.Comput. Graph. Forum2972010, 2021-2028URL: http://hal.inria.fr/inria-00524555/enback to text
  • 35 articleS.Stefan Bruckner and M. E.Meister Eduard Gröller. Style Transfer Functions for Illustrative Volume Rendering.Comput. Graph. Forum2632007, 715-724URL: http://www.cg.tuwien.ac.at/research/publications/2007/bruckner-2007-STF/back to text
  • 36 inproceedingsC.Chris Buehler, M.Michael Bosse, L.Leonard McMillan, S.Steven Gortler and M.Michael Cohen. Unstructured lumigraph rendering.Proc. ACM SIGGRAPH2001, 425-432URL: http://doi.acm.org/10.1145/383259.383309DOIback to text
  • 37 articleO.Ozan Cakmakci, S.Sophie Vo, K. P.Kevin P. Thompson and J. P.Jannick P. Rolland. Application of radial basis functions to shape description in a dual-element off-axis eyewear display: Field-of-view limit.J. Society for Information Display16112008, 1089-1098DOIback to text
  • 38 articleE.Eva Cerezo, F.Frederic Perez-Cazorla, X.Xavier Pueyo, F.Francisco Seron and F. X.François Xavier Sillion. A Survey on Participating Media Rendering Techniques.The Visual Computer2005HALback to text
  • 39 inproceedingsJ.Jiazhou Chen, X.Xavier Granier, N.Naiyang Lin and Q.Qunsheng Peng. On-Line Visualization of Underground Structures using Context Features.Symposium on Virtual Reality Software and Technology (VRST)ACM2010, 167-170URL: http://hal.inria.fr/inria-00524818/enDOIback to text
  • 40 articleJ.Jiazhou Chen, G.Gaël Guennebaud, P.Pascal Barla and X.Xavier Granier. Non-oriented MLS Gradient Fields.Computer Graphics ForumDecember 2013, URL: http://hal.inria.fr/hal-00857265back to text
  • 41 articleO.Oliver Cossairt, S.Shree Nayar and R.Ravi Ramamoorthi. Light field transfer: global illumination between real and synthetic objects.ACM Trans. Graph.2732008, URL: http://doi.acm.org/10.1145/1360612.1360656DOIback to textback to textback to textback to text
  • 42 articleF.F. Cuny, L.L. Alonso and N.Nicolas Holzschuch. A novel approach makes higher order wavelets really efficient for radiosity.Comput. Graph. Forum1932000, 99-108back to text
  • 43 articleE.Eugene D'Eon and G.Geoffrey Irving. A quantized-diffusion model for rendering translucent materials.ACM Trans. Graph.3042011, URL: http://doi.acm.org/10.1145/2010324.1964951DOIback to text
  • 44 inproceedingsK. J.Kristin J. Dana, B.Bram van Ginneken, S.Shree Nayar and J. J.Jan J. Koenderink. Reflectance and texture of real-world surfaces.IEEE Conference on Computer Vision and Pattern Recognition (ICCV)1997, 151-157back to text
  • 45 articleY.Yue Dong, J.Jiaping Wang, F.Fabio Pellacini, X.Xin Tong and B.Baining Guo. Fabricating spatially-varying subsurface scattering.ACM Trans. Graph.2942010, URL: http://doi.acm.org/10.1145/1778765.1778799DOIback to text
  • 46 bookP.Philip Dutré, K.Kavita Bala and P.Philippe Bekaert. Advanced Global Illumination.A.K. Peters2006back to textback to text
  • 47 articleK.Kevin Egan, F.Florian Hecht, F.Frédo Durand and R.Ravi Ramamoorthi. Frequency analysis and sheared filtering for shadow light fields of complex occluders.ACM Trans. Graph.3022011, URL: http://doi.acm.org/10.1145/1944846.1944849DOIback to text
  • 48 articleK.Kevin Egan, Y.-T.Yu-Ting Tseng, N.Nicolas Holzschuch, F.Frédo Durand and R.Ravi Ramamoorthi. Frequency Analysis and Sheared Reconstruction for Rendering Motion Blur.ACM Trans. Graph.2832009, URL: http://hal.inria.fr/inria-00388461/enDOIback to textback to textback to text
  • 49 articleR.Roland Fleming, A.Antonio Torralba and E. H.Edward H. Adelson. Specular reflections and the perception of shape.J. Vis.492004, 798-820URL: http://journalofvision.org/4/9/10/back to text
  • 50 inproceedingsA.Abhijeet Ghosh, S.Shruthi Achutha, W.Wolfgang Heidrich and M.Matthew O'Toole. BRDF Acquisition with Basis Illumination.IEEE International Conference on Computer Vision (ICCV)2007, 1-8back to text
  • 51 articleM.Michael Goesele, X.Xavier Granier, W.Wolfgang Heidrich and H.-P.Hans-Peter Seidel. Accurate Light Source Acquisition and Rendering.ACM Trans. Graph.2232003, 621-630URL: http://hal.inria.fr/hal-00308294DOIback to textback to text
  • 52 inproceedingsC. M.Cindy M. Goral, K. E.Kenneth E. Torrance, D. P.Donald P. Greenberg and B.Bennett Battaile. Modeling the interaction of light between diffuse surfaces.Proc. ACM SIGGRAPH1984, 213-222back to text
  • 53 articleM.Milos Hasan, M.Martin Fuchs, W.Wojciech Matusik, H.Hanspeter Pfister and S.Szymon Rusinkiewicz. Physical reproduction of materials with specified subsurface scattering.ACM Trans. Graph.2942010, URL: http://doi.acm.org/10.1145/1778765.1778798DOIback to textback to text
  • 54 phdthesisP. S.Paul S. Heckbert. Simulating Global Illumination Using Adaptative Meshing.University of California1991back to text
  • 55 articleM. B.Matthias B. Hullin, M.Martin Fuchs, I.Ivo Ihrke, H.-P.Hans-Peter Seidel and H. P.Hendrik P. A. Lensch. Fluorescent immersion range scanning.ACM Trans. Graph.2732008, URL: http://doi.acm.org/10.1145/1360612.1360686DOIback to text
  • 56 articleM. B.Matthias B. Hullin, J.Johannes Hanika, B.Boris Ajdin, H.-P.Hans-Peter Seidel, J.Jan Kautz and H. P.Hendrik P. A. Lensch. Acquisition and analysis of bispectral bidirectional reflectance and reradiation distribution functions.ACM Trans. Graph.2942010, URL: http://doi.acm.org/10.1145/1778765.1778834DOIback to text
  • 57 articleM. B.Matthias B. Hullin, H. P.Hendrik P. A. Lensch, R.Ramesh Raskar, H.-P.Hans-Peter Seidel and I.Ivo Ihrke. Dynamic Display of BRDFs.Comput. Graph. Forum3022011, 475--483URL: http://dx.doi.org/10.1111/j.1467-8659.2011.01891.xDOIback to textback to textback to textback to text
  • 58 articleI.Ivo Ihrke, K. N.Kiriakos N. Kutulakos, H. P.Hendrik P. A. Lensch, M.Marcus Magnor and W.Wolfgang Heidrich. Transparent and Specular Object Reconstruction.Comput. Graph. Forum2982010, 2400-2426back to text
  • 59 inproceedingsI.Ivo Ihrke, I.Ilya Reshetouski, A.Alkhazur Manakov, A.Art Tevs, M.Michael Wand and H.-P.Hans-Peter Seidel. A Kaleidoscopic Approach to Surround Geometry and Reflectance Acquisition.IEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW)IEEE Computer Society2012, 29-36back to textback to textback to text
  • 60 inproceedingsI.Ivo Ihrke, G.Gordon Wetzstein and W.Wolfgang Heidrich. A theory of plenoptic multiplexing.IEEE Conf. Computer Vision and Pattern Recognition (CVPR)\bf oralIEEE Computer Society2010, 483-490back to textback to text
  • 61 inproceedingsJ. T.James T. Kajiya. The rendering equation.Proc. ACM SIGGRAPH1986, 143-150URL: http://doi.acm.org/10.1145/15922.15902DOIback to textback to text
  • 62 inproceedingsJ.Jan Kautz, P.-P.Peter-Pike Sloan and J.John Snyder. Fast, arbitrary BRDF shading for low-frequency lighting using spherical harmonics.Proc. Eurographics workshop on Rendering (EGWR)Pisa, Italy2002, 291-296back to text
  • 63 articleI.Ilhan Kaya, K. P.Kevin P. Thompson and J. P.Jannick P. Rolland. Edge clustered fitting grids for -polynomial characterization of freeform optical surfaces.Opt. Express19272011, 26962-26974URL: http://www.opticsexpress.org/abstract.cfm?URI=oe-19-27-26962DOIback to text
  • 64 articleM.Michael Kolomenkin, I.Ilan Shimshoni and A.Ayellet Tal. Demarcating curves for shape illustration.ACM Trans. Graph. (SIGGRAPH Asia)2752008, URL: http://doi.acm.org/10.1145/1409060.1409110DOIback to text
  • 65 articleM.Marc Levoy, Z.Zhengyun Zhang and I.Ian McDowall. Recording and controlling the 4D light field in a microscope using microlens arrays.J. Microscopy23522009, 144-162URL: http://dx.doi.org/10.1111/j.1365-2818.2009.03195.xDOIback to text
  • 66 articleS.Shen Li, G.Gaël Guennebaud, B.Baoguang Yang and J.Jieqing Feng. Predicted Virtual Soft Shadow Maps with High Quality Filtering.Comput. Graph. Forum3022011, 493-502URL: http://hal.inria.fr/inria-00566223/enback to text
  • 67 articleC.-K.Chia-Kai Liang, T.-H.Tai-Hsu Lin, B.-Y.Bing-Yi Wong, C.Chi Liu and H. H.Homer H. Chen. Programmable aperture photography: multiplexed light field acquisition.ACM Trans. Graph.2732008, URL: http://doi.acm.org/10.1145/1360612.1360654DOIback to text
  • 68 articleY.Yanli Liu and X.Xavier Granier. Online Tracking of Outdoor Lighting Variations for Augmented Reality with Moving Cameras.IEEE Transactions on Visualization and Computer Graphics184March 2012, 573-580URL: http://hal.inria.fr/hal-00664943DOIback to textback to text
  • 69 articleW.Wojciech Matusik and H.Hanspeter Pfister. 3D TV: a scalable system for real-time acquisition, transmission, and autostereoscopic display of dynamic scenes.ACM Trans. Graph.2332004, 814-824URL: http://doi.acm.org/10.1145/1015706.1015805DOIback to textback to textback to text
  • 70 articleW.Wojciech Matusik, H.Hanspeter Pfister, M.Matt Brand and L.Leonard McMillan. A data-driven reflectance model.ACM Trans. Graph.2232003, 759-769URL: http://doi.acm.org/10.1145/882262.882343DOIback to text
  • 71 inproceedingsG.Gero Müller, J.Jan Meseth, M.Mirko Sattler, R.Ralf Sarlette and R.Reinhard Klein. Acquisition, Synthesis and Rendering of Bidirectional Texture Functions.Eurographics 2004, State of the Art Reports2004, 69-94back to text
  • 72 inproceedingsA.Andy Ngan, F.Frédo Durand and W.Wojciech Matusik. Experimental Analysis of BRDF Models.Proc. Eurographics Symposium on Rendering (EGSR)2005, 117-226back to text
  • 73 bookF. E.F. E. Nicodemus, J. C.J. C. Richmond, J. J.J. J. Hsia, I. W.I. W. Ginsberg and T.T. Limperis. Geometrical Considerations and Nomenclature for Reflectance.National Bureau of Standards1977back to text
  • 74 articleM.Matthew O'Toole and K. N.Kiriakos N. Kutulakos. Optical computing for fast light transport analysis.ACM Trans. Graph.2962010back to text
  • 75 articleR.Romain Pacanowski, X.Xavier Granier, C.Christophe Schlick and P.Pierre Poulin. Volumetric Vector-based Representation for Indirect Illumination Caching.J. Computer Science and Technology (JCST)2552010, 925-932URL: http://hal.inria.fr/inria-00505132/enDOIback to text
  • 76 articleR.Romain Pacanowski, O.Oliver Salazar-Celis, C.Christophe Schlick, X.Xavier Granier, P.Pierre Poulin and A.Annie Cuyt. Rational BRDF.IEEE Transactions on Visualization and Computer Graphics1811February 2012, 1824-1835URL: http://hal.inria.fr/hal-00678885DOIback to textback to textback to text
  • 77 articleP.Pieter Peers, D.Dhruv Mahajan, B.Bruce Lamond, A.Abhijeet Ghosh, W.Wojciech Matusik, R.Ravi Ramamoorthi and P.Paul Debevec. Compressive light transport sensing.ACM Trans. Graph.2812009back to text
  • 78 articleB.Benjamin Petit, J.-D.Jean-Denis Lesage, C.Clément Menier, J.Jérémie Allard, J.-S.Jean-Sébastien Franco, B.Bruno Raffin, E.Edmond Boyer and F.François Faure. Multicamera Real-Time 3D Modeling for Telepresence and Remote Collaboration.Int. J. digital multimedia broadcasting2010Article ID 247108, 12 pages2010, URL: http://hal.inria.fr/inria-00436467DOIback to text
  • 79 articleR.Ravi Ramamoorthi and P.Pat Hanrahan. On the relationship between radiance and irradiance: determining the illumination from images of a convex Lambertian object.J. Opt. Soc. Am. A18102001, 2448-2459back to text
  • 80 articleR.Ravi Ramamoorthi, D.Dhruv Mahajan and P.Peter Belhumeur. A first-order analysis of lighting, shading, and shadows.ACM Trans. Graph.2612007, URL: http://doi.acm.org/10.1145/1189762.1189764DOIback to textback to textback to text
  • 81 bookR.Ramesh Raskar and J.Jack Tumblin. Computational Photography: Mastering New Techniques for Lenses, Lighting, and Sensors.A K Peters/CRC Press2012back to text
  • 82 bookE.Erik Reinhard, W.Wolfgang Heidrich, P.Paul Debevec, S.Sumanta Pattanaik, G.Greg Ward and K.Karol Myszkowski. High Dynamic Range Imaging: Acquisition, Display and Image-Based Lighting.2nd editionMorgan Kaufmann Publishers2010back to text
  • 83 articleP.Peiran Ren, J.Jiaping Wang, J.John Snyder, X.Xin Tong and B.Baining Guo. Pocket reflectometry.ACM Trans. Graph.3042011back to text
  • 84 articleP.Patrick Reuter, G.Guillaume Riviere, N.Nadine Couture, S.Stéphanie Mahut and L.Loïc Espinasse. ArcheoTUI-Driving virtual reassemblies with tangible 3D interaction.J. Computing and Cultural Heritage322010, 1-13URL: http://hal.inria.fr/hal-00523688/enDOIback to text
  • 85 articleH. E.Holly E. Rushmeier and K. E.Kenneth E. Torrance. The zonal method for calculating light intensities in the presence of a participating medium.ACM SIGGRAPH Comput. Graph.2141987, 293-302URL: http://doi.acm.org/10.1145/37402.37436DOIback to text
  • 86 inproceedingsS.Szymon Rusinkiewicz. A New Change of Variables for Efficient BRDF Representation.Proc. EGWR '981998, 11-22back to text
  • 87 inproceedingsP.Peter Schröder and W.Wim Sweldens. Spherical wavelets: efficiently representing functions on the sphere.Proc. ACM SIGGRAPHannual conference on Computer graphics and interactive techniques1995, 161-172URL: http://doi.acm.org/10.1145/218380.218439back to text
  • 88 bookF. X.François Xavier Sillion and C.Claude Puech. Radiosity and Global Illumination.Morgan Kaufmann Publishers1994back to text
  • 89 articleC.Cyril Soler, K.Kartic Subr, F.Frédo Durand, N.Nicolas Holzschuch and F. X.François Xavier Sillion. Fourier Depth of Field.ACM Transactions on Graphics2822009, URL: http://hal.inria.fr/inria-00345902DOIback to text
  • 90 articleM.Marc Stamminger, A.Annette Scheel, X.Xavier Granier, F.Frédéric Perez-Cazorla, G.George Drettakis and F. X.François Xavier Sillion. Efficient Glossy Global Illumination with Interactive Viewing.Computer Graphics Forum1912000, 13-25back to text
  • 91 articleM.Michael Stark, J.James Arvo and B.Brian Smits. Barycentric Parameterizations for Isotropic BRDFs.IEEE Trans. Vis. and Comp. Graph.1122005, 126-138URL: http://dx.doi.org/10.1109/TVCG.2005.26back to text
  • 92 bookW.William Thompson, R.Roland Fleming, S.Sarah Creem-Regehr and J. K.Jeanine Kelly Stefanucci. Visual Perception from a Computer Graphics Perspective.A K Peters/CRC Press2011back to textback to text
  • 93 articleY.-T.Yu-Ting Tsai and Z.-C.Zen-Chung Shih. All-Frequency Precomputed Radiance Transfer Using Spherical Radial Basis Functions and Clustered Tensor Approximation.ACM Trans. Graph.2532006, 967-976back to text
  • 94 inproceedingsD.David Vanderhaeghe, R.Romain Vergne, P.Pascal Barla and W.William Baxter. Dynamic Stylized Shading Primitives.Proc. Int. Symposium on Non-Photorealistic Animation and Rendering (NPAR)ACM2011, 99-104URL: http://hal.inria.fr/hal-00617157/enback to textback to text
  • 95 articleP.Peter Vangorp, J.Jurgen Laurijssen and P.Philip Dutré. The influence of shape on the perception of material reflectance.ACM Trans. Graph.2632007, URL: http://doi.acm.org/10.1145/1276377.1276473DOIback to text
  • 96 inproceedingsE.Eric Veach and L. J.Leonidas J. Guibas. Metropolis light transport.Proc. SIGGRAPH '97annual conference on Computer graphics and interactive techniquesACM/Addison-Wesley Publishing Co.1997, 65-76URL: http://doi.acm.org/10.1145/258734.258775back to text
  • 97 articleR.Romain Vergne, P.Pascal Barla, R.Roland Fleming and X.Xavier Granier. Surface Flows for Image-based Shading Design.ACM Trans. Graph.3132012, URL: http://hal.inria.fr/hal-00702280back to textback to text
  • 98 articleR.Romain Vergne, R.Romain Pacanowski, P.Pascal Barla, X.Xavier Granier and C.Christophe Schlick. Improving Shape Depiction under Arbitrary Rendering.IEEE Trans. Visualization and Computer Graphics1782011, 1071-1081URL: http://hal.inria.fr/inria-00585144/enDOIback to textback to textback to text
  • 99 articleR.Romain Vergne, R.Romain Pacanowski, P.Pascal Barla, X.Xavier Granier and C.Christophe Schlick. Light warping for enhanced surface depiction.ACM Trans. Graph.283\it front cover2009, 25:1URL: http://doi.acm.org/10.1145/1531326.1531331DOIback to text
  • 100 articleR.Romain Vergne, D.David Vanderhaeghe, J.Jiazhou Chen, P.Pascal Barla, X.Xavier Granier and C.Christophe Schlick. Implicit Brushes for Stylized Line-based Rendering.Comput. Graph. Forum302\bf 3\textsuperscript{rd} best paper award2011, 513-522URL: http://hal.inria.fr/inria-00569958/enDOIback to text
  • 101 articleF.Forest Vincent, L.Loïc Barthe, G.Gaël Guennebaud and M.Mathias Paulin. Soft Textured Shadow Volume.Comput. Graph. Forum2842009, 1111-1120URL: http://hal.inria.fr/inria-00390534/enback to text
  • 102 articleJ.Jiaping Wang, Y.Yue Dong, X.Xin Tong, Z.Zhouchen Lin and B.Baining Guo. Kernel Nyström method for light transport.ACM Trans. Graph.2832009back to text
  • 103 articleB.Baoguang Yang, J.Jieqing Feng, G.Gaël Guennebaud and X.Xinguo Liu. Packet-based Hierarchical Soft Shadow Mapping.Comput. Graph. Forum2842009, 1121-1130URL: http://hal.inria.fr/inria-00390541/enback to text