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
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,  

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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.