2025‌Activity reportProject-TeamMANAO‌​‌

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  62,‌​‌ 36 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  74​​​‌ and Light-Field rendering  34‌). 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​‌  73, 75,​​ 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  95​‌ 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.

Auto-stereoscopy display​​​‌	HDR display	Printing both​ geometry and material
©Nintendo​‌	©Dolby Digital	54

Examples​​ of new display technologies​​​‌

With the​‌ evolution of measurement and​​ display technologies that go​​​‌ beyond conventional images (e.g.,​ as illustrated in Figure​‌ 1, High-Dynamic Range​​ Imaging  85, stereo​​​‌ displays or new display​ technologies  58, and​‌ physical fabrication  25,​​ 43, 54)​​​‌ the frontiers between real​ and virtual worlds are​‌ vanishing  39. 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

Interactions/Transfers​​ between real and virtual​​​‌ worlds.

3.1​​​‌ Related Scientific Domains

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  44​ 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  59,​‌ 60 and display  58​​ 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  46 or differential‌ analysis  83, 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  87, 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  55​‌ in order to develop​​ tailored strategies  100.​​​‌ For instance, starting from​ simple direct lighting, more​‌ complex phenomena have been​​ progressively introduced: first diffuse​​​‌ indirect illumination  52,​ 91, then more​‌ generic inter-reflections  62,​​ 44 and volumetric scattering​​​‌  88, 41.​ 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  40.‌​‌ The numerical complexity explodes​​ when considering directional properties​​​‌ of light transport such‌ as radiance intensity (Watt‌​‌ per square meter and​​ per steradian - $\mathrm{W‌}.m^{-\mathrm{2‌}}.s{r}^{-‌‌1}$), reducing the​​ possibility to simulate or​​​‌ accurately represent some optical‌ phenomena. For instance, Haar‌​‌ wavelets have been extended​​ to the spherical domain​​​‌  90 but are difficult‌ to extend to non-piecewise-constant‌​‌ data  93. More​​ recently, researches prefer the​​​‌ use of Spherical Radial‌ Basis Functions  96 or‌​‌ Spherical Harmonics  82.​​ For more complex data,​​​‌ such as reflective properties‌ (e.g., BRDF  76,‌​‌ 63 - 4D), ray-space​​ (e.g., Light-Field  72 -​​​‌ 4D), spatially varying reflective‌ properties (6D - 86‌​‌), new models, and​​ representations are still investigated​​​‌ such as rational functions‌  79 or dedicated models‌​‌  27 and parameterizations  89​​, 94. 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  79.​​​‌

Texuring	1st order‌ gradient field	Environment reflection‌​‌	2st order gradient​​ field

Firts-order analysis

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  83​​​‌ and frequency analysis  46​). 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​  48 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.​

Light-Field transfer

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  72, 58​. We consider projecting​‌ systems and surfaces  35​​, for personal use,​​​‌ virtual reality and augmented​ reality  30. 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  56,​​ 28, 57,​​​‌ 60. 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​  61.

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  60​‌, 81). Similarly,​​ increasing the number of​​​‌ viewpoints is a way​ toward the creation of​‌ full 3D displays  72​​. 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., 80, 107‌).

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.  39‌​‌. 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  70 are one‌​‌ of the key technologies​​ to develop such acquisition​​​‌ (e.g., Light-Field camera 1‌ 61 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  68.​​​‌ More generally, by designing‌ unified optical and digital‌​‌ systems  77, 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  79​​​‌. Second, we have‌ to integrate signals from‌​‌ multiple sensors (such as​​ GPS, accelerometer, ...) to​​​‌ prevent some computation (e.g.,‌ 71). Finally, the‌​‌ experience of the group​​ in surface modeling help​​​‌ the design of optical‌ surfaces  64 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

Realistic​	Rendering	Visualization	and Illustration​‌
(a) Global illumination 78​​	(b) Shadows 110	(c)​​​‌ Shape enhancement 102	(d)​ Shape depiction 26

Rendering​‌ techniques from realistic solutions​​ to more expressive ones.​​​‌

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  104​, 66 or stylized​‌ shading  33, 102​​ 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  26 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  105‌​‌, motion blur  46​​, depth of field​​​‌  92, 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  69​​​‌, 45. 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  37.​​ Independent image processing for​​​‌ each viewpoint may disturb‌ the feeling of depth‌​‌ by introducing inconsistent information​​ in each images. Finally,​​​‌ more dedicated displays  58‌ 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  3832​‌. 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)​	(b)	(c)	(d)	(e)​‌	(f)

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

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., 98):​​​‌ 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  98),‌ 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.

4.1 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.

5.1 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​ is engaged in several​‌ actions and initiatives related​​ to the environmental issues​​​‌ within the research and​ higher-education domain:

• Ecoinfo: He​‌ 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:​ He 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 and​​​‌ external computing ressources within​ their carbon footprint estimation​‌ tool (GES1point5).​​ The first version of​​​‌ the module has been​ released in October 2021.​‌
• He participates in the​​ elaboration and dissemination of​​​‌ an introductory course to​ climate change issues and​‌ environnemental impacts of ICT,​​ with two colleagues of​​​‌ the LaBRI.

7.1 Latest​‌ software developments

7.2​​​‌ New platforms

7.2.1 La‌ Coupole

Participants: Romain Pacanowski‌​‌, Jérémie Ettedgui,​​ Clément Joubert, Pierre​​​‌ Mézières, François Margall‌, Louis De Oliveira‌​‌.

   

View of La​​ Coupole

La​​ Coupole is a measurement​​​‌ device that acquires spatially-varying‌ reflectance function (SV-BRDF) on‌​‌ non-planar object which area​​ can be up to​​​‌ 1.5m${}^2$.

Its‌ main characteristics are:

• RGB‌​‌ 12MP Camera (100 fps)​​
• 6-axes Robot
• 1080 White​​​‌ LED
• 3D Laser Scanner‌ Laser: 200 $\mu \mathrm{m‌‌}$ resolution
• Maximal Measurement Area:​​ 1.75 m${}^2$
• Optical​​​‌ Resolution: 50 $\mu \mathrm{m‌}$

Left, official poster‌​‌ of the Exhibition Textiles​​ 3D presented to the​​​‌ museum of Ethnography of‌ Bordeaux. 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.​​​‌

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 continue to be‌​‌ used in the projects​​​‌ VESPAA, AUTOMATA, xDDiff and​ TOL.

During 2025, La​‌ Coupole was upgraded in​​ terms of hardware, in​​​‌ particular to reduce problems​ related to the cable​‌ connecting the camera to​​ the control PC. The​​​‌ solution developed and deployed​ (see Figure 11)​‌ involves embedding a mini-PC,​​ such as an OrangePi,​​​‌ which is powered by​ an internal connection to​‌ the robot and transmits​​ the acquired images asynchronously​​​‌ via a dedicated Wi-Fi​ network. A second mprovement​‌ is the replacement of​​ the Ximea sensor with​​​‌ a new, more sensitive​ sensor from JAI.

Gilet​‌ de Femme	Ceinture	Manteau​​

Examples of numerical reconstructions​​​‌ from data acquired with​ La Coupole.

Photograph of inside La​ Coupole showing the new​‌ embedded mini-PC and the​​ new camera.

7.2.2​​​‌ HYPERION: Measuring Bidirectional Subscattering​ Reflectance and Transmission Functions​‌

Participants: Morgane Gerardin,​​ Romain Pacanowski.

A​​​‌ new platform (cf. Figure​ 12), hyperion, 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​ 13).

The platform​‌ has been validated with​​ a publication in the​​​‌ journal Optics Express 49​

The BSSxDF measurement platform.​‌

Measurement principle

7.3 Open​‌ data

8.1 Analysis​​ and Simulation

8.1.1 Efficient​​ Modeling and Rendering of​​​‌ Iridescence from Cholesteric Liquid‌ Crystals

Participants: Gary Fourneau‌​‌, Pascal Barla,​​ Romain Pacanowski.

We​​​‌ introduce a novel approach‌ to the efficient modeling‌​‌ and rendering of Cholesteric​​ Liquid Crystals (CLCs), materials​​​‌ known for producing colorful‌ effects due to their‌​‌ helical molecular structure. CLCs​​ reflect circularly-polarized light within​​​‌ specific spectral bands, making‌ their accurate simulation challenging‌​‌ for realistic rendering in​​ Computer Graphics. In this​​​‌ paper 16, using‌ the two-wave approximation from‌​‌ the Photonics literature, we​​ develop a piecewise spectral​​​‌ reflectance model that improves‌ the understanding of how‌​‌ light interact with CLCs​​ for arbitrary incident angles.​​​‌ Our reflectance model allows‌ for more efficient spectral‌​‌ rendering and fast integration​​ into RGB-based rendering engines.​​​‌ We show that our‌ approach is able to‌​‌ reproduce the unique visual​​ properties of both natural​​​‌ and man-made CLCs, while‌ keeping the computation fast‌​‌ enough for interactive applications​​ and avoiding potential spectral​​​‌ aliasing issues.

Rendering of‌ CLC structures

8.2 Rendering, Visualization and‌​‌ Illustration

8.2.1 Importance Sampling​​ of the Micrograin Visible​​​‌ NDF

Participants: Simon Lucas‌, Romain Pacanowski,‌​‌ Pascal Barla.

Importance​​ sampling of visible normal​​​‌ distribution functions (vNDF) is‌ a required ingredient for‌​‌ the efficient rendering of​​ microfacet‐based materials. In this​​​‌ paper 10, we‌ explain how to sample‌​‌ the vNDF for the​​ micrograin material model, which​​​‌ has been recently improved‌ to handle height‐normal correlations‌​‌ through a new Geometric​​ Attenuation Factor (GAF), leading​​​‌ to a stronger impact‌ on appearance compared to‌​‌ the earlier Smith approximation.​​ To this end, we​​​‌ make two contributions: we‌ derive analytic expressions for‌​‌ the marginal and conditional​​ cumulative distribution functions (CDFs)​​​‌ of the vNDF; we‌ provide efficient methods for‌​‌ inverting these CDFs based​​ respectively on a 2D​​​‌ lookup table and on‌ the triangle‐cut method.

Importance‌​‌ Sampling of the Micrograin​​ Visible NDF

8.2.2 A Fluorescent Material​​ Model for Non-Spectral Editing​​​‌ & Rendering

Participants: Laurent‌ Belcour [Intel, Grenoble],‌​‌ Alban Fichet [Intel, Grenoble]​​, Pascal Barla.​​​‌

Fluorescent materials are characterized‌ by a spectral reradiation‌​‌ toward longer wavelengths. Recent​​ work has shown that​​​‌ the rendering of fluorescence‌ in a non-spectral engine‌​‌ is possible through the​​​‌ use of appropriate reduced​ reradiation matrices. But the​‌ approach has limited expressivity,​​ as it requires the​​​‌ storage of one reduced​ matrix per fluorescent material,​‌ and only works with​​ measured fluorescent assets. In​​​‌ this work 15,​ we introduce an analytical​‌ approach to the editing​​ and rendering of fluorescence​​​‌ in a non-spectral engine.​ It is based on​‌ a decomposition of the​​ reduced reradiation matrix, and​​​‌ an analytically-integrable Gaussian-based model​ of the fluorescent component.​‌ The model reproduces the​​ appearance of fluorescent materials​​​‌ accurately, especially with the​ addition of a UV​‌ basis. Most importantly, it​​ grants variations of fluorescent​​​‌ material parameters in real-time,​ either for the editing​‌ of fluorescent materials, or​​ for the dynamic spatial​​​‌ variation of fluorescence properties​ across object surfaces. A​‌ simplified one-Gaussian fluorescence model​​ even allows for the​​​‌ artist-friendly creation of plausible​ fluorescent materials from scratch,​‌ requiring only a few​​ reflectance colors as input.​​​‌

A Fluorescent Material Model​ for Non-Spectral Editing &​‌ Rendering

8.3 Editing and​​ Modeling

8.3.1 Inbetweening with​​​‌ Occlusions for Non-Linear Rough​ 2D Animation

Participants: Melvin​‌ Even, Pierre Bénard​​, Pascal Barla.​​​‌

Representing 3D motion and​ depth through 2D animated​‌ drawings is a notoriously​​ difficult task, requiring time​​​‌ and expertise when done​ by hand. Artists must​‌ pay particular attention to​​ occlusions and how they​​​‌ evolve through time, a​ tedious process. Computer-assisted inbetweening​‌ methods such as cut-out​​ animation tools allow for​​​‌ such occlusions to be​ handled beforehand using a​‌ 2D rig, at the​​ expense of flexibility and​​​‌ artistic expression. In this​ work 9, we​‌ extend the flexible 2D​​ animation framework of Even​​​‌ et al. 47 to​ handle occlusions. We do​‌ so by retaining three​​ key properties of their​​​‌ system that are crucial​ to speed-up the animation​‌ process: input rough drawings,​​ real-time preview, and non-linear​​​‌ animation editing. Our contribution​ is two-fold: a fast​‌ method to compute 2D​​ masks from rough drawings​​​‌ with a semi-automatic dynamic​ layout system for occlusions​‌ between drawing parts; and​​ an artist-friendly method to​​​‌ both automatically and manually​ control the dynamic visibility​‌ of strokes for self-occlusions.​​ Such controls are not​​​‌ available in any traditional​ 2D animation software especially​‌ with rough drawings. Our​​ system helps artists produce​​​‌ convincing 3D-like 2D animations​ (Figure 17), including​‌ head turns, foreshortening effects,​​ out-of-plane rotations, overlapping volumes​​​‌ and even transparency.

Head-turn​ animation produced with our​‌ rough 2D animation system​​

8.3.2 Trajectory-aware Smears‌ for Stylized 3D Animations‌​‌

Participants: Lou Tremolieres,​​ Jean Basset, Pierre​​​‌ Bénard, Pascal Barla‌.

Smearing is an‌​‌ essential effect to expressively​​ convey motion in stylized​​​‌ animations. In this paper‌ 20, we extend‌​‌ the method of Basset​​ et al. 29 to​​​‌ better emphasize the main‌ motion's trajectory of an‌​‌ object when generating elongated​​ in-betweens, i.e., when stretching​​​‌ a 3D object along‌ its trajectory to cover‌​‌ adjacent frames. This limits​​ visual artifacts such as​​​‌ intersections that typically occur‌ when trajectories self-overlap due‌​‌ to local rotations or​​ abrupt changes of direction​​​‌ (trajectories with high curvatures‌ or even discontinuities at‌​‌ contacts). We address these​​ cases with minor computational​​​‌ and memory overheads, and‌ offer enhanced impact expressiveness‌​‌ by combining smear and​​ squash-and-stretch effects at collisions.​​​‌

3D jumping animation stylized‌ with smear frames created‌​‌ with our method (elongated​​ in-betweens, motion lines, multiple​​​‌ in-betweens)

8.3.3 Complex System​​​‌ Exploration with Interactive Human‌ Guidance

Participants: Bastien Morel‌​‌, Clément Moulin-Frier,​​ Pascal Barla.

The​​​‌ diversity of patterns that‌ emerge from complex systems‌​‌ motivates their use for​​ scientific or artistic purposes.​​​‌ When exploring these systems,‌ the challenges faced are‌​‌ the size of the​​ parameter space and the​​​‌ strongly non-linear mapping between‌ parameters and emerging patterns.‌​‌ In addition, artists and​​ scientists who explore complex​​​‌ systems do so with‌ an expectation of particular‌​‌ patterns. Taking these expectations​​ into account adds a​​​‌ new set of challenges,‌ which the exploration process‌​‌ must address. In this​​ paper 19, we​​​‌ provide design choices and‌ their implementation to address‌​‌ these challenges; enabling the​​ maximization of the diversity​​​‌ of patterns discovered in‌ the user's region of‌​‌ interest – which we​​ call the constrained diversity​​​‌ – in a sample-efficient‌ manner. The region of‌​‌ interest is expressed in​​ the form of explicit​​​‌ constraints. These constraints are‌ formulated by the user‌​‌ in a system-agnostic way,​​ and their addition enables​​​‌ interactive system exploration leading‌ to constrained diversity, while‌​‌ maintaining global diversity.

Complex​​​‌ system exploration

8.4​​​‌ Sustainability studies

8.4.2 Setting​​ reference GHG emissions for​​​‌ research activities

Participants: Gaël​ Guennebaud, Léa Marquet​‌, Valentin Bellassen [CESAER]​​, David Makowski [MIA​​​‌ Paris-Saclay], Tamara Ben-Ari​ [UMR Innovation].

The​‌ carbon footprint of academic​​ research has attracted growing​​​‌ attention in recent years,​ with numerous assessments conducted​‌ at the level of​​ universities or research departments.​​​‌ Yet, methodological inconsistencies and​ small sample sizes limit​‌ comparability and hinder generalization,​​ while concrete mitigation targets​​​‌ remain underdeveloped. This study​ 11 draws on a​‌ national database covering about​​ 157,000 research staff in​​​‌ 700 units-roughly one-third of​ French public research-between 2019​‌ and 2023. Emissions are​​ assessed across five major​​​‌ sources: purchases, professional travel,​ commuting, electricity, and heating.​‌ The dataset is used​​ to (i) model structural​​​‌ determinants of research-related GHG​ emissions and (ii) establish​‌ reference values to guide​​ mitigation strategies (Figure 20​​​‌). We develop a​ framework to identify robust​‌ statistical models to predict​​ average emissions levels per​​​‌ source. Based on staff​ composition, supervisory body, research​‌ domain, and geographical location,​​ these models explain up​​​‌ to one-third of inter-unit​ variance and improve predictive​‌ accuracy by 8%–23% over​​ baseline averages. Embedded in​​​‌ an online tool, these​ models help support the​‌ design of efficient, equitable,​​ and realistic mitigation targets.​​

Graphics of average mitigation​​​‌ potentials per emission source‌ and per research domain.‌​‌

9.1 Bilateral contracts‌​‌ with industry

10.1 European initiatives​​​‌

10.1.1 Other european programs/initiatives​

ERCIM xDDiff Project (2024-2027)​‌

Participants: Morgane Gérardin,​​ Pierre Mézière, Romain​​​‌ Pacanowski.

As part​ of the xDDiff activities,​‌ we participated in a​​ workshop held on December​​​‌ 2, 2025, at the​ Physikalisch-Technische Bundesanstalt (PTB, German​‌ National Metrology Institute), where​​ we presented “La Coupole:​​​‌ Spatially varying measurement system​ for 3D objects” (to​‌ appear in HAL) introduced​​ the "La Coupole" measurement​​​‌ setup and presented results​ obtained from data acquired​‌ with the system.

Furthermore,​​ we also presented "Metrological​​​‌ characterization of translucency :​ from planar materials to​‌ complex objects" (to appear​​ in HAL). In addition,​​​‌ during the progress meeting​ on December 3–4, 2025,​‌ we presented “Fit of​​ BRDF data from the​​​‌ CSIC”, focusing on BRDF​ fitting results obtained from​‌ measurement data provided by​​ laboratories of the CSIC​​​‌ (Spanish National Research Council).​

ECCH Automata Project (2025-2029)​‌

Participants: Clément Joubert,​​ Romain Pacanowski.

EU-funded​​​‌ AUTOMATA will transform this​ process by enabling low-cost​‌ and time-efficient digitisation. Using​​ AI-augmented robotics and sensors,​​​‌ AUTOMATA will create 3D​ models enriched with archaeometric​‌ data, providing a practical​​ and cost-effective solution for​​​‌ digitisation. Robotic tools with​ newly developed AI methodologies​‌ will improve the digitisation​​ process of visible and​​​‌ non-visible properties of archaeological​ finds, enhance the robustness​‌ and efficiency of 3D​​ digitisation, improve surface appearance​​​‌ acquisition, and integrate 2D​ representations. This approach streamlines​‌ data acquisition, aided by​​ human-AI collaboration, and, in​​​‌ turn, the collection of​ big, well-identified data will​‌ empower the development of​​ AI models. This cost-effective​​​‌ technology will democratise access​ to digitisation, benefiting museums​‌ and smaller institutions, aid​​ preservation methods and restorers’​​​‌ work, and foster inclusive​ knowledge-sharing via a dedicated​‌ crowdsourcing platform. Finally, the​​ data collected by AUTOMATA​​​‌ will ensure seamless integration​ of data into the​‌ ECCCH Cloud and facilitate​​ data sharing and innovative​​​‌ usage strategies by CCIs.​

Inria has joined the​‌ project in July 2025​​ and has started working​​​‌ with La Coupole on​ photogrammetric acquisition (cf. Figure​‌ 21). This will​​ help to design and​​​‌ conceive the final acquisition​ system.

Top: Photograph taken​‌ using La Coupole of​​ a litic object. Right:​​​‌ 3D digitized object after​ applying a photogrammetry method​‌ using 80 photographs.

Top:​​ Photograph taken using La​​ Coupole of a litic​​​‌ object. Right: 3D digitized‌ object after applying a‌​‌ photogrammetry method using 80​​ photographs.

10.2 National‌​‌ initiatives

10.3 Regional​​​‌ initiatives

11.1 Promoting scientific activities‌

11.2 Teaching​ - Supervision - Juries​‌ - Educational and pedagogical​​ outreach

11.3 Popularization‌​‌

12.1‌ Major publications

• 1 article‌​‌L.Laurent Belcour and​​ P.Pascal Barla.​​​‌ A Practical Extension to‌ Microfacet Theory for the‌​‌ Modeling of Varying Iridescence​​.ACM Transactions on​​​‌ Graphics364July‌ 2017, 65HAL‌​‌DOI
• 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 articleM.Morgane​​ Gerardin, M.Mathias​​​‌ Paulin and R.Romain‌ Pacanowski. Imaging device‌​‌ to measure the reflective​​ and transmissive part of​​​‌ isotropic BSSRDF.Optics‌ Express3222October‌​‌ 2024, 39267-39292HAL​​DOI
• 4 articleN.​​​‌Nicolas Holzschuch and R.‌Romain Pacanowski. A‌​‌ Two-Scale Microfacet Reflectance Model​​ Combining Reflection and Diffraction​​​‌.ACM Transactions on‌ Graphics364Article‌​‌ 66July 2017,​​ 12HALDOI
• 5​​​‌ 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
• 6‌​‌ articleG.Georges Nader​​ and G.Gaël Guennebaud​​​‌. Instant Transport Maps‌ on 2D Grids.‌​‌ACM Transactions on Graphics​​376November 2018​​​‌, 13HALDOI‌
• 7 articleA.Alexandra‌​‌ Schmid, P.Pascal​​ Barla and K.Katja​​​‌ Doerschner. Material category‌ of visual objects computed‌​‌ from specular image structure​​.Nature Human Behaviour​​​‌77July 2023‌, 1152-1169HALDOI‌​‌
• 8 articleK.Kevin​​​‌ Vynck, R.Romain​ Pacanowski, A.Adrian​‌ Agreda, A.Arthur​​ Dufay, X.Xavier​​​‌ Granier and P.Philippe​ Lalanne. The visual​‌ appearances of disordered optical​​ metasurfaces.Nature Materials​​​‌21May 2022,​ 1035-1041HALDOI

12.2​‌ Publications of the year​​

12.3 Cited publications

• 25​​​‌ 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
• 26 article​​L.Lucas Ammann,​​​‌ P.Pascal Barla,‌ X.Xavier Granier,‌​‌ G.Gaël Guennebaud and​​ P.Patrick Reuter.​​​‌ Surface Relief Analysis for‌ Illustrative Shading.Computer‌​‌ Graphics Forum314​​​‌June 2012, 1481-1490​URL: http://hal.inria.fr/hal-00709492DOIback​‌ to textback to​​ text
• 27 techreportM.​​​‌Michael Ashikhmin and S.​Simon Premoze. Distribution-based​‌ BRDFs.unpublishedUniv.​​ of Utah2007back​​​‌ to text
• 28 article​B.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.27​​52008back to​​​‌ text
• 29 inproceedingsJ.​Jean Basset, P.​‌Pierre Bénard and P.​​Pascal Barla. SMEAR:​​​‌ Stylized Motion Exaggeration with​ ARt-direction.SIGGRAPH Conference​‌ Papers '24Denver, CO​​ / Virtual, United States​​​‌July 2024HALDOI​back to textback​‌ to text
• 30 book​​O.Oliver Bimber and​​​‌ R.Ramesh Raskar.​ Spatial Augmented Reality: Merging​‌ Real and Virtual Worlds​​.A K Peters/CRC​​​‌ Press2005back to​ textback to text​‌
• 31 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)30​​42011, URL:​​​‌ http://www-sop.inria.fr/reves/Basilic/2011/BCRA11back to text​
• 32 articleS.Simon​‌ Boyé, G.Gaël​​ Guennebaud and C.Christophe​​​‌ Schlick. Least Squares​ Subdivision Surfaces.Comput.​‌ Graph. Forum297​​2010, 2021-2028URL:​​​‌ http://hal.inria.fr/inria-00524555/enback to text​
• 33 articleS.Stefan​‌ Bruckner and M. E.​​Meister Eduard Gröller.​​​‌ Style Transfer Functions for​ Illustrative Volume Rendering.​‌Comput. Graph. Forum26​​32007, 715-724​​​‌URL: http://www.cg.tuwien.ac.at/research/publications/2007/bruckner-2007-STF/back to​ text
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