Signal Processing Laboratory, EPFL
October 26, 2007, 14:15, Room GC B3 424 (click here for the map)
Scene understanding with multiple modalities has been one of the main focus of several research communities. Low-cost digital cameras and the progress to process large data sets such as digital images have promoted the development of vision-based analysis. In this talk, current trends to detect and track objects of interest in a scene with digital cameras will be discussed. A novel framework will be described to take advantage of multiple fixed and mobile cameras to enhance the performance of the system. Advantages to deal with fixed cameras and challenges to use mobile ones will be discussed.
Alexandre Alahi was born in Lyon, France, in August 1981. He received the M.S. degree in Communication Systems from the Swiss Federal Institute of Technology, Lausanne, Switzerland, in 2006. During his studies, he earned a one year exchange fellowship to study at Carnegie Mellon University, Pittsburgh, PA, USA. He has working experience in the field of image processing and computer vision in various companies. Among them, we can cite Logitech (Silicon Valley-CA, USA), and Mitsubishi Electric Research Laboratories (Cambridge � MA, USA). At Logitech, in 2004, he reduced the cost of their webcam by optimizing the processing of their color processing pipe. From September 2005 to March 2006, at Mitsubishi Electric Research Laboratories, he developed a 3D scene simulator to measure the performance of scheduling algorithms to control pan-tilt-zoom cameras. He is now working towards his Ph.D. degree in scene understanding with multiple moving and fixed cameras.