Imaging Components, Systems, and Processing

Object tracking with double-dictionary appearance model

[+] Author Affiliations
Li Lv, Zhen Sun, Lizhong Xu

Hohai University, College of Computer and Information, No. 8 Focheng West Road, JiangNing District, Nanjing, JiangSu Province 210098, China

Tanghuai Fan, Jun Wang

Nanchang Institute of Technology, School of Information Engineering, No. 289 Tianxiang Road, Hi tech Development Zone, Nanchang, Jiangxi Province 330099, China

Opt. Eng. 55(8), 083106 (Aug 18, 2016). doi:10.1117/1.OE.55.8.083106
History: Received April 8, 2016; Accepted July 27, 2016
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Abstract.  Dictionary learning has previously been applied to target tracking across images in video sequences. However, most trackers that use dictionary learning neglect to make optimal use of the representation coefficients to locate the target. This increases the possibility of losing the target in the presence of similar objects, or in case occlusion or rotation occurs. We propose an effective object-tracking method based on a double-dictionary appearance model under a particle filter framework. We employ a double dictionary by training template features to represent the target. This representation not only exploits the relationship between the candidate and target but also represents the target more accurately with minimal residual. We also introduce a simple and effective strategy to update the template to reduce the influence of occlusion, rotation, and drift. Experiments on challenging sequences showed that the proposed algorithm performs favorably against the state-of-the-art methods in terms of several comparative metrics.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Li Lv ; Tanghuai Fan ; Zhen Sun ; Jun Wang and Lizhong Xu
"Object tracking with double-dictionary appearance model", Opt. Eng. 55(8), 083106 (Aug 18, 2016). ; http://dx.doi.org/10.1117/1.OE.55.8.083106


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