Robust Object Tracking with Compressive Sensing and Patches Matching

被引:4
作者
Pi, Jiatian [1 ]
Hu, Keli [2 ]
Zhang, Xiaolin [1 ]
Gu, Yuzhang [1 ]
Zhan, Yunlong [1 ]
机构
[1] SIMIT, Shanghai 200050, Peoples R China
[2] Shaoxing Univ, Shaoxing 312000, Peoples R China
关键词
object tracking; compressive sensing; patches matching; feature extraction;
D O I
10.1587/transinf.2015EDL8235
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1720 / 1723
页数:4
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