A Visual Tracking Framework for Intent Recognition in Videos

Authors:
Alireza Tavakkoli;Richard Kelley;Christopher King;Mircea Nicolescu;Monica Nicolescu;George Bebis
Affiliations:
Department of Computer Science and Engineering, University of Nevada, Reno,;Department of Computer Science and Engineering, University of Nevada, Reno,;Department of Computer Science and Engineering, University of Nevada, Reno,;Department of Computer Science and Engineering, University of Nevada, Reno,;Department of Computer Science and Engineering, University of Nevada, Reno,;Department of Computer Science and Engineering, University of Nevada, Reno,
Venue:
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Year:
2008

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Abstract

To function in the real world, a robot must be able to understand human intentions. This capability depends on accurate and reliable detection and tracking of trajectories of agents in the scene. We propose a visual tracking framework to generate and maintain trajectory information for all agents of interest in a complex scene. We employ this framework in an intent recognition system that uses spatio-temporal contextual information to recognize the intentions of agents acting in different scenes, comparing our system with the state of the art.