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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
Publication Date: 2016/06/01
Online ISSN: 1745-1361
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.