2/10/14: Amit K. Roy Chowdhury 


Situation Awareness from Wide-Area Vision Networks

Amit K. Roy Chowdhury 
University of California, Riverside

Abstract. Over the past decade, large-scale camera networks have become increasingly prevalent in a wide range of applications, such as security and surveillance, disaster response, and environmental modeling. However, the analysis of the acquired videos has been largely manual and post-facto. Thus, the development of algorithms capable of analyzing a scene covering a wide area is extremely important. In this talk, we will focus on three inter-related problems in this domain.
i)      The performance of the analysis algorithms often suffers because of the inability to effectively acquire the desired images. We will discuss our recent work on integrated sensing and analysis in a distributed camera network so as to maximize various scene-understanding performance criteria (e.g., tracking accuracy, best shot, and image resolution). We will show how the existing work in autonomous multiagent systems can be leveraged for this purpose - more specifically, game theory-based distributed optimization algorithms for dynamic camera network reconfiguration.
ii)     In application domains where there is no central processor accumulating all the data (e.g., disaster response), inferences have to be drawn through local decisions at the camera nodes and negotiations with the neighbors. We will present our work on distributed reasoning in vision networks, especially the recently proposed Information Weighted Consensus Filter (ICF). The application of ICF to multi-target tracking will then be presented.
iii)    Finally, we will address the issue of higher-level scene understanding. The recognition of activities in video is an essential step in this regard. Activities happening over a wide-area are often related in space and time. We will show how graphical inference methods can be used to robustly recognize such activities, specifically taking into account the contextual relationships between them.

Amit K. Roy Chowdhury received his undergraduate degree in electrical engineering from Jadavpur University, Calcutta, India, his Masters degree in systems science and automation from the Indian Institute of Science, Bangalore, India, and the Ph.D. degree in electrical engineering from the University of Maryland, College Park. He is a Professor of Electrical Engineering and a Cooperating Faculty in the Department of Computer Science at the University of California, Riverside. His broad research interests include the areas of image processing and analysis, computer vision, and statistical signal processing and pattern recognition. Together with his students and collaborators, he has over 100 technical publications in these areas, including one best student paper award. His current research projects include intelligent camera networks, wide-area scene analysis, motion analysis in video, activity recognition and search, video-based biometrics (face and gait), and biological video analysis. He is the first author of the book - Camera Networks: The Acquisition and Analysis of Videos over Wide Areas - the first research monograph on this topic. He has been on the organizing and program committees of multiple computer vision and image processing conferences and is serving on the editorial boards of multiple journals.

No comments:

Post a Comment

Note: Only a member of this blog may post a comment.