CASIA OpenIR  > 模式识别国家重点实验室  > 先进数据分析与学习
Visual Tracking via Manifold Regularized Local Structured Sparse Representation Model
Wang, Lingfeng; Pan, Chunhong
2015
Conference NameICIP 2015
Source PublicationICIP 2015
Conference Date2015
Conference PlaceQuebec, Canada
AbstractIn this paper, we propose a new visual tracking method via the manifold regularized local structured sparse representation model under the particle filtering tracking framework. First, in order to tackle the difficulties of partial occlusion and illumination variation, the local structured sparse representation model is incorporated by exploiting both partial and spatial information of the target. Second, the manifold regularization is used to ensure that neighboring particles should share similar representation coefficients, so that these particles can cooperate with each other. Extensive experiments are performed on various video sequences, showing improvement over the state-of-the-art approaches.
KeywordVisual Tracking Sparse Representation Manifold Regularization
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11025
Collection模式识别国家重点实验室_先进数据分析与学习
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
Wang, Lingfeng,Pan, Chunhong. Visual Tracking via Manifold Regularized Local Structured Sparse Representation Model[C],2015.
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