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.
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Tavakkoli, A., Kelley, R., King, C., Nicolescu, M., Nicolescu, M., Bebis, G. (2008). A Visual Tracking Framework for Intent Recognition in Videos. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_43
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DOI: https://doi.org/10.1007/978-3-540-89639-5_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89638-8
Online ISBN: 978-3-540-89639-5
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