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An Improved Real Time Compressive Tracking
Xu, Rui; Gu, Xiaodong; Wei, Benjie; Xu, R (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, Beijing, Peoples R China.
Department空间技术部
Source Publication2013 SECOND IAPR ASIAN CONFERENCE ON PATTERN RECOGNITION (ACPR 2013)
2013
Pages692-696
Language英语
ISBN978-1-4799-2190-4
AbstractRecently, an algorithm called compressive tracking is utilized to cope with real time tracking, which use a very sparse measurement matrix to compress samples of targets and background, and then a classifier is trained to distinguish foreground and background. However, compressive tracking extracts foreground features that are limited to the current frame and does not consider the samples of previous frames in its learning procedure. This paper presents a novel enhanced compressive tracking, which extracts two kinds of samples of targets: current samples and previous samples. Our method use targets information from the previous and current frames to train a novel classifier which composes of two weighted classifiers based on different sample bags. Experimental results demonstrate the effectiveness and robustness of our method.
KeywordObject Tracking Sample Bags Sparse Matrix Online Learning
Conference Name2nd IAPR Asian Conference on Pattern Recognition (ACPR)
Conference DateNOV 05-08, 2013
Conference PlaceNaha, JAPAN
Indexed ByEI ; CPCI
Document Type会议论文
Identifierhttp://ir.nssc.ac.cn/handle/122/4732
Collection空间技术部
Corresponding AuthorXu, R (reprint author), Chinese Acad Sci, Natl Space Sci Ctr, Beijing, Peoples R China.
Recommended Citation
GB/T 7714
Xu, Rui,Gu, Xiaodong,Wei, Benjie,et al. An Improved Real Time Compressive Tracking[C]:IEEE COMPUTER SOC,2013:692-696.
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