Crowd analysis is an emerging topic in computer vision, being closely related to image processing, machine learning and multiple object tracking. Advances in this field benefit to a variety of problems, which may be more conceptual, such as graph modelling for collective motion analysis, or more practical, such as improving the security of specific locations such as railway stations or stadium exits.
For more information about the context of the internship, visit the project webpage:
Master level or equivalent, with solid background in computer science and software design. Familiarity with GPU programming and computer vision will be appreciated, as well as previous experience with WebGL or equivalent libraries.
As soon as possible, but no later than March 2018.
 N. Pellicanò, E. Aldea, and S. Le Hégarat-Mascle, “Geometry-based multiple camera head detection in dense crowds,” in Proceedings of the 28th British Machine Vision Conference (BMVC) - 5th Activity Monitoring by Multiple Distributed Sensing Workshop, 2017.
(c) GdR 720 ISIS - CNRS - 2011-2018.