Research

Imaging the Brain Microstructure
Diffusion tensor imaging, the most common model of the diffusion signal, is unable to represent the signal arising from water molecules diffusing in different compartments such as multiple fascicles and the extra-axonal space. Multi-fascicle models overcome this limitation by providing a parametric representation for each compartment, allowing the development of new brain network modeling.
Sep 19, 2017
Video Segmentation
Image/video segmentation aims at partitioning the visual frames into non-overlapping areas with different semantical contents. It has tremendous applications in data compression, tracking, augmented reality, activity or object recognition, video annotation and video retrieval. Our group focus on fast and efficient segmentation methods, in such a way to extract content with high-level of abstraction from videos.
Sep 1, 2017
Sport player foreground detector reinforcement through visual texture classification
In the context of sport events, this project deals with the improvement of a player detector based on a foreground detector. It considers some visual texture features in order to discriminate true from false detections.
Sep 1, 2017
Fusion-based techniques to enhance images and videos
One of the most successful image fusion strategies is based on the Laplacian pyramid decomposition. In the context of multi-scale fusion, the Laplacian pyramid decomposition has recently been demonstrated to be effective for several challenging tasks to enhance images and videos.
Sep 1, 2017
Detection of facial expressions and CG animation
This work is aimed at developing a semi-automate system to animate facial expressions. The system consists of detection of facial expressions and Computer Graphics animations of a facial charactor.
Sep 1, 2017
Automatic Team Sport Coverage
Computer vision tools drive the automatic and democratic production of sport events video reports, by using scene analysis to select an appropriate viewpoint in a static and/or dynamic multi-camera infrastructure.
Sep 1, 2017

Ball detection and tracking: Foreground detector reinforcement through trajectory analysis
In the context of team sport events monitoring, the various phases of the game must be delimited and interpreted. In the case of a basketball game, the detection and the tracking of the ball are mandatory. However, one of the difficulties is that the ball is often occluded by players. This project deals with the detection of the ballistic trajectory of a ball thrown between two players or toward the basket. Ballistic trajectories are build on the 3D ball candidates previously detected at each time-stamp from a foreground detector.
Sep 1, 2016

Consistent Basis Pursuit in Quantized Compressed Sensing
This project focuses on the estimation of low-complexity signals when they are observed through M uniformly quantized compressive observations. Among such signals, we consider 1-D sparse vectors, low-rank matrices, or compressible signals that are well approximated by one of these two models. In this context, we prove the estimation efficiency of a variant of Basis Pursuit Denoise, called Consistent Basis Pursuit (CoBP), enforcing consistency between the observations and the re-observed estimate, while promoting its low-complexity nature.
Oct 1, 2015

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