Recent research activities
3D vision with non simultaneous exposure cameras
For computer vision applications with motion, the non-simultaneous exposure of pixels introduces geometric distortions that make the classical SfM algorithms imprecise or even unusable, as is the case with Rolling Shutter cameras or linescan systems. Our work allows us to take these distortions into account and/or to compensate them.
Rolling Shutter Homography and its applications (T-PAMI 2020) https://yizhenlao.github.io/files/RSHomo_PAMI2020.pdf
Rolling Shutter SfM using analogies with non-rigid SfM (IJCV 2020) https://yizhenlao.github.io/files/Lao_et_al-2020-International_Journal_of_Computer_Vision.pdf
Rolling Shutter compensation using straigtness constraint (CVPR 2018) https://yizhenlao.github.io/files/3871_final.pdf
Calibration of panoramic line scan cameras (CVIU 2019) https://www.sciencedirect.com/science/article/abs/pii/S1077314219300049
3D vision using plenoptic cameras
The design of plenoptic cameras is usually complex and relies on precise placement of optic elements. Several calibration procedures have been but relying on simplified models, reconstructed images to extract features, or multiple calibrations when several types of micro-lens are used. We propose a new calibration method and explore the use of such cameras in 3D vision.
Blur Aware Calibration of Multi-Focus Plenoptic Camera (CVPR 2020) https://openaccess.thecvf.com/content_CVPR_2020/papers/Labussiere_Blur_Aware_Calibration_of_Multi-Focus_Plenoptic_Camera_CVPR_2020_paper.pdf
3D reconstruction by camera and MMW radar fusion
The combination of a camera and a depth sensor is widely used for 3D reconstruction. Most often, it is LiDAR, structured light or time-of-flight camera. We show that with fine modeling and precise calibration, a MMW camera/radar system provides a good quality 3D map.
Accurate calibration of a camera/radar rig (ICRA 2015) https://www.researchgate.net/profile/Raphael_Rouveure/publication/282951724_Radar_and_vision_sensors_calibration_for_outdoor_3D_reconstruction/links/562f2e6408ae04c2aeb63e7f/Radar-and-vision-sensors-calibration-for-outdoor-3D-reconstruction.pdf
3D reconstruction using a camera/radar sensor (Sensors 2O15) https://www.mdpi.com/1424-8220/15/10/25937/htm
Ptolémée : Automatic deep brain segmentation using MRI and deep learning (I am a partner of this project driven by Prof. J-J Lemaire from Clermont Ferrand Hospital (CHU))
Three-dimensional tracking of monodisperse TRAjectories by Quantitative measurements (TRAQ) (I am a partner of this ANR project coordinated by Prof. P Biwolé)