IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Robust Object Tracking with Compressive Sensing and Patches Matching
Jiatian PIKeli HUXiaolin ZHANGYuzhang GUYunlong ZHAN
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2016 Volume E99.D Issue 6 Pages 1720-1723

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Abstract
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.
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© 2016 The Institute of Electronics, Information and Communication Engineers
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