Robust Online Multi-Object Tracking based on Tracklet Confidence and Online Discriminative Appearance Learning

CVPR 2014 Seung-Hwan BaeKuk-Jin Yoon

Online multi-object tracking aims at producing complete tracks of multiple objects using the information accumulated up to the present moment. It still remains a difficult problem in complex scenes, because of frequent occlusion by clutter or other objects, similar appearances of different objects, and other factors... (read more)

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