Pascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He then worked at SRI International and INRIA Sophia-Antipolis as a Computer Scientist. He joined EPFL in 1996 where he is now a Professor in the School of Computer and Communication Science and heads the Computer Vision Laboratory.
His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded two spinoff companies (Pix4D and PlayfulVision).
The research activities of the Computer Vision Laboratory focus on shape and motion recovery from images, object and people detection and tracking in video sequences, and analysis of brain microscopy image-stacks. CVLab also provides undergraduate and graduate teaching and performs technology transfer to both established and start up companies.
Pascal Fua's research is sponsored by the Swiss National Science Foundation, the CTI, the European Union including a senior ERC grant, and several industrial partners.
Fields of expertise
All since 1996
|R. Achanta, A. Shaj, K. Smith, A. Lucchi, P. Fua, and S. S�sstrunk.
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, num. 11, p. 2274 - 2282, 2012.
|SLIC Superpixels Compared to State-of-the-art Superpixel Methods|
|F Fleuret, J Berclaz, R Lengagne, and P Fua
Pattern Analysis and Machine Intelligence, 30 (2), 267-282, 2008
|Multicamera People Tracking with a Probabilistic Occupancy Map|
|V. Lepetit and P. Fua
Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, Nr. 9, pp. 1465--1479, 2006.
|Keypoint Recognition using Randomized Trees|
|P. Fua and Y. G. Leclerc
International Journal of Computer Vision, Vol. 16, pp. 35-56, 1995.
|Object-Centered Surface Reconstruction: Combining Multi-Image Stereo and Shading|
Machine Vision and Applications, Vol. 6, Nr. 1, pp. 35-49, 1993.
|A Parallel Stereo Algorithm that Produces Dense Depth Maps and Preserves Image Features|