Learning Multi-Task Correlation Particle Filters for Visual Tracking

In this paper, we propose a multi-task correlation particle filter (MCPF) for robust visual tracking. We first present the multi-task correlation filter (MCF) that takes the interdependencies among different object parts and features into account to learn the correlation filters jointly. Next, the p...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2019-02, Vol.41 (2), p.365-378
Hauptverfasser:	Zhang, Tianzhu, Xu, Changsheng, Yang, Ming-Hsuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computational modeling Correlation correlation filter Occlusion Optical tracking particle filter Robustness State estimation State of the art structural modeling Target tracking Task analysis Visual tracking Visualization
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