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Proceedings Paper

Discussion among different methods of updating model filter in object tracking
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Paper Abstract

Discriminative correlation filters (DCF) have recently shown excellent performance in visual object tracking area. In this paper we summarize the methods of updating model filter from discriminative correlation filter (DCF) based tracking algorithms and analyzes similarities and differences among these methods. We deduce the relationship among updating coefficient in high dimension (kernel trick), updating filter in frequency domain and updating filter in spatial domain, and analyze the difference among these different ways. We also analyze the difference between the updating filter directly and updating filter’s numerator (object response power) with updating filter’s denominator (filter’s power). The experiments about comparing different updating methods and visualizing the template filters are used to prove our derivation.

Paper Details

Date Published: 19 February 2018
PDF: 9 pages
Proc. SPIE 10608, MIPPR 2017: Automatic Target Recognition and Navigation, 106080E (19 February 2018); doi: 10.1117/12.2285038
Show Author Affiliations
Taihang Dong, Huazhong Univ. of Science and Technology (China)
Sheng Zhong, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 10608:
MIPPR 2017: Automatic Target Recognition and Navigation
Jianguo Liu; Jayaram K. Udupa; Hanyu Hong, Editor(s)

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