Section: Bilateral Contracts and Grants with Industry

Grants with Industry

CIFRE contract with Orange on Generalized lifting for video compression

Participants : Christine Guillemot, Bihong Huang.

• Title  : Generalized lifting for video compression.

• Research axis : §  6.3.5 .

• Partners : Orange Labs, Inria-Rennes, UPC-Barcelona.

• Funding : Orange Labs.

• Period : Apr.2012-Mar.2015.

This contract with Orange labs. (started in April. 2012) concerns the PhD of Bihong Huang and aims at modelling the redundancy which remains in spatial and temporal prediction residues. The analysis carried out in the first year of the PhD has shown that this redundancy (hence the potential rate saving) is high. In 2013, different methods have been investigated to remove this redundancy, such as generalized lifting and different types of predictors. The generalized lifting is an extension of the lifting scheme of classical wavelet transforms which permits the creation of nonlinear and signal probability density function (pdf) dependent and adaptive transforms. This study is also carried out in collaboration with UPC (Prof. Philippe Salembier) in Barcelona.

CIFRE contract with Orange on 3D quality assessment

Participants : Darya Khaustova, Olivier Le Meur.

• Title  : Objective Evaluation of 3D Video Quality.

• Research axis : §  6.1.3 .

• Partners : Orange Labs, Inria-Rennes.

• Funding : Orange Labs.

• Period : Dec.2011-Nov.2014.

This contract with Orange labs. (starting in Dec. 2011) concerns the PhD of Darya Khaustova and aims at developping a video quality metric for 3D content. The usage of 3D video is expected to increase in the next years. In order to ensure a good QoE (Quality of Experience), the 3D video quality must be monitored and accuratly measured. The goal of this thesis is to study objective measures suitable for estimating 3D video quality. A comparison with ground truth as well as with the state-of-the-art 2D metrics should be carried out. To be as effective as possible, the feature of the human visual system should be taken into account.

CIFRE contract with Technicolor on High Dynamic Range (HDR) video compression

Participants : Mikael Le Pendu, Christine Guillemot.

• Title  : Floating point high dynamic range (HDR) video compression

• Research axis : §  6.3.4 .

• Partners : Technicolor, Inria-Rennes.

• Funding : Technicolor, ANRT.

• Period : Dec.2012-Nov.2015.

High Dynamic Range (HDR) images contain more intensity levels than traditional image formats, leading to higher volumes of data. HDR images can represent more accurately the range of intensity levels found in real scenes, from direct sunlight to faint starlight. The goal of the thesis is to design a visually lossless compression algorithm for HDR floating-point imaging data. The first year of the thesis has been dedicated to the design of a quantization method converting the floating point data into a reduced bit depth representation, with minimal loss. The method leads to a bit rate saving of $50\%$ compared to the existing Adaptive LogLuv transform.

CIFRE contract with Technicolor on sparse modelling of spatio-temporal scenes

Participants : Martin Alain, Christine Guillemot.

• Title  : Spatio-temporal analysis and characterization of video scenes

• Research axis : §  6.1.4 .

• Partners : Technicolor, Inria-Rennes.

• Funding : Technicolor, ANRT.

• Period : Oct.2012-Sept.2015.

A first CIFRE contract has concerned the Ph.D of Safa Cherigui from Nov.2009 to Oct.2012, in collaboration with Dominique Thoreau (Technicolor). The objective was to investigate texture and video scene characterization using models based on sparse and data dimensionality reduction techniques, as well as based on epitomes. The objective was then to use these models and methods in different image processing problems focusing in particular on video compression. While, the first PhD thesis has focused on spatial analysis, processing, and prediction of image texture, a second CIFRE contract (PhD thesis of Martin Alain) has started in Oct. 2012 to push further the study by addressing issues of spatio-temporal analysis and epitome construction, with applications to temporal prediction, as well as to other video processing problems such as denoising and super-resolution.

CIFRE contract with Thomson Video Networks (TVN) on Video analysis for HEVC based video coding

Participants : Nicolas Dhollande, Christine Guillemot, Olivier Le Meur.

• Title  : Coding optimization of HEVC by using pre-analysis approaches.

• Research axis : §  6.3.5 .

• Partners : Thomson Video Networks, Univ. Rennes 1.

• Funding : Thomson Video Networks (TVN).

• Period : Nov.2012-Sept.2015.

This contract with TVN (started in Oct. 2012) concerns the PhD of Nicolas Dhollande and aims at performing a coding mode analysis and developing a pre-analysis software. HEVC standard is a new standard of compression including new tools such as advanced prediction modes. Compared to the previous standard H.264, HEVC's complexity is three to four times higher. The goal of this thesis is to infer the best coding decisions (prediction modes...) in order to reduce the computational complexity of HEVC thanks to a pre-analysis step. The pre-analysis is expected to provide useful estimates of local video characteristics which will then help selecting the prediction and transform partitions as well as a number of other parameters such as the quantization parameters or the prediction modes.