Robust Object Tracking with Compressive Sensing and Patches Matching

Jiatian PI
Keli HU
Xiaolin ZHANG
Yuzhang GU
Yunlong ZHAN

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
object tracking,  compressive sensing,  patches matching,  feature extraction,  

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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.