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We address the problem of group-level event recognition from videos. The events of interest are defined based on the motion and interaction of members in a group over time. Example events include group formation, dispersion, following, chasing, flanking, and fighting. To recognize these complex group events, we propose a novel approach that learns the group-level scenario context from automatically...
This paper addresses the challenge of recognizing behavior of groups of individuals in unconstraint surveillance environments. As opposed to approaches that rely on agglomerative or decisive hierarchical clustering techniques, we propose to recognize group interactions without making hard decisions about the underlying group structure. Instead we use a probabilistic grouping strategy evaluated from...
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