Summary and data subjects : The goal of this project is to develop a pipeline for merging images from Cameras and point clouds from LiDAR sensors in order to realize precise 3D obstacle detection and tracking using deep learning techniques. Description : Camera sensors are common sensor for the perception of autonomous agents. Providing dense color information,…
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Summary and data subjects : In the research field of active upper limb prosthesis, one of the main issue is the human machine interface. The state of the art is focused for years on a solution to acquire the intention of the subject in order to develop an accurate control of robotic prosthesis. The most promising…
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Summary and data subjects : The thesis is focused on learning a complex manipulation robotics task using little knowledge. More precisely, the concerned task consists in reaching an object with a serial arm and the objective is to learn it without camera calibration parameters, forward kinematics, handcrafted features, or expert demonstrations. Deep reinforcement learning algorithms suit…
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Description : The artificial vision algorithms used road context may be impacted by adverse weather conditions. It is therefore necessary to improve these algorithms for use in such conditions. In addition, applications developed to operate in road situations require perfectly reliable operation even in adverse weather conditions. Many works allow weather classification, but they do not…
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Summary and data subjects : Deep learning and artificial intelligence have brought revolutionary advance to the computer vision industry. The overall subject of this project is to improve the user experience of virtual cosmetic product simulation applications (make-up, skin diag, hair coloration etc.). The first part of this project consists of improving the visual simulation effects…
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Summary and data subjects : This project has been funded and carried by Renault Group because the perception in AD (Autonomous Driving) and ADAS (Advanced Driving Assistance Systems) still fails in many user cases despite tremendous efforts in both industrial and research laboratories, and despite huge system’s complexity and computation load. The future of mobility, even autonomous,…
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ComSee – for COMputers that SEE – is a Computer Vision research team of the Image, Systems of Perception and Robotics (ISPR) department of the Pascal Institute. ComSee research activities mainly focus on two axes: 3D vision and geometry: vision sensor modeling and calibration (including standard, rolling-shutter, and plenoptic cameras), 3D localisation and 3D reconstruction…
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