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We propose and experimentally evaluate a new method for clustering human behaviors that is suitable for bootstrapping an anomaly detection module for intelligent video surveillance systems. The method uses dynamic time warping, agglomerative hierarchical clustering, and hidden Markov models to provide an initial partitioning of a set of observation sequences then automatically identifies where to...
In many automated visual surveillance applications, humans are important targets. As humans often move together, occlusions between them occur frequently, and it brings difficulty into image analysis. In this paper, two novel techniques are proposed to divide an image blob where two people are connected due to partial occlusion between them. The first technique uses a simple human size model to distinguish...
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