文献类型：期刊文献

英文题名：Robust Object Tracking with Compressive Sensing and Patches Matching

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

年份：2016

卷号：E99D

期号：6

起止页码：1720

外文期刊名：IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS

收录：SCI-EXPANDED(收录号：WOS:000381562200041)、、EI(收录号：20170203243831)、Scopus(收录号：2-s2.0-85009154241)、WOS

语种：英文

外文关键词：object tracking; compressive sensing; patches matching; feature extraction

外文摘要：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.