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Robust Object Tracking with Compressive Sensing and Patches Matching Jiatian PI Keli HU Xiaolin ZHANG Yuzhang GU Yunlong ZHAN Publication IEICE TRANSACTIONS on Information and Systems Vol.E99-D No.6 pp.1720-1723 Publication Date: 2016/06/01 Publicized: 2016/02/26 Online ISSN: 1745-1361 DOI: 10.1587/transinf.2015EDL8235 Type of Manuscript: LETTER Category: Image Recognition, Computer Vision Keyword: object tracking, compressive sensing, patches matching, feature extraction, Full Text: PDF>>
Summary: Object tracking is one of the fundamental problems in computer vision. However, there is still a need to improve the overall capability in various tracking circumstances. In this letter, a patches-collaborative compressive tracking (PCCT) algorithm is presented. Experiments on various challenging benchmark sequences demonstrate that the proposed algorithm performs favorably against several state-of-the-art algorithms. | |||||
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