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R-LAIR: Riverside Lab for Artificial Intelligence Research

Social Grouping for Target Handover in Multi-View Video (2013)

by Zhen Qin, Christian R. Shelton, and Lunshao Chai

Abstract: This paper uses a social grouping model to improve target handover across multiple non-overlapping cameras to enable wide-area video understanding. Prior work focuses on modeling appearance and spatial-temporal cues for target handover. In cameras with different conditions, these cues are weak, at best. We provide a complete generative social grouping model which generalizes a recent single-camera case. Our extension requires strengthening the probabilistic interpretations and the resulting optimization over track handovers and social groupings can be formulated in terms of standard fast algorithms. We demonstrate the effectiveness of the method over existing techniques on challenging real-world multi-camera video.


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Zhen Qin, Christian R. Shelton, and Lunshao Chai (2013). "Social Grouping for Target Handover in Multi-View Video." IEEE International Conference on Multimedia and Expo. pdf      

Bibtex citation

@inproceedings{QinSheCha13,
   author = "Zhen Qin and Christian R. Shelton and Lunshao Chai",
   title = "Social Grouping for Target Handover in Multi-View Video",
   booktitle = "IEEE International Conference on Multimedia and Expo",
   booktitleabbr = "ICME",
   year = 2013,
}

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