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We propose a hybrid framework to address the problem of tracking multiple articulated humans from a single camera. Our method incorporates offline learned category-level detector with online learned instance-specific detector as a hybrid system. To deal with humans in large pose articulation, which can not be reliably detected by off-line trained detectors, we propose an online learned instance specific...
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous approaches that use linear motion methods only, we online build a non-linear motion map to better explain direction changes and produce more robust motion affinities between tracklets. Moreover, based on the incremental...
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