CASIA OpenIR  > 精密感知与控制研究中心  > 精密感知与控制
Visual Tracking via Saliency Weighted Sparse Coding Appearance Model
Li, Wanyi1; Wang, Peng1; Qiao, Hong2
2014
Conference NameInternational Conference on Pattern Recognition (ICPR)
Source PublicationInternational Conference on Pattern Recognition (ICPR)
Issue
Pages4092-4097
Conference Date2014
Conference PlaceStockholm
AbstractSparse coding has been used for target appearance modeling and applied successfully in visual tracking. However, noise may be inevitably introduced into the representation due to background clutter. To cope with this problem, we propose a saliency weighted sparse coding appearance model for visual tracking. Firstly, a spectral filtering based visual attention computational model, which combines both bottom-up and top-down visual attention, is proposed to calculate saliency map. Secondly, pooling operation in sparse coding is weighted by calculated saliency map to help target representation focus on distinctive features and suppress background clutter. Extensive experiments on a recently proposed tracking benchmark demonstrate that the proposed algorithm outperforms state-of-the-art methods in tracking objects under background clutter.
KeywordVisual Tracking Saliency Visual Attention Sparse Coding
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/4818
Collection精密感知与控制研究中心_精密感知与控制
Corresponding AuthorLi, Wanyi
Affiliation1.Research Center of Precision Sensing and Control Institute of Automation, Chinese Academy of Sciences
2.State Key Laboratory of Management and Control for Complex Systems Institute of Automation, Chinese Academy of Sciences
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li, Wanyi,Wang, Peng,Qiao, Hong. Visual Tracking via Saliency Weighted Sparse Coding Appearance Model[C],2014:4092-4097.
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