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Information Technology Journal
Year: 2013  |  Volume: 12  |  Issue: 23  |  Page No.: 7117 - 7123

Exploiting a Reliable Structural Appearance Model for Visual Tracking with Sparse Representation

Hainan Zhao and Xuan Wang    

Abstract: This study proposes a novel approach of exploiting a reliable structural appearance model for visual tracking. The proposed method samples overlapped local image patches within the target region and evaluates the reliabilities of these local patches respectively by introducing a sample based local sparse representation for each local patch. The occluded or deteriorative patches are excluded, only the stable ones are employed to construct a reliable structural appearance model, which is used for likelihood computation. In addition, the reliability evaluation of local patch facilitates our selective update scheme, by which we reduce the influence of the occluded target template and alleviate the drift problem. Experiments on challenging video sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-the-art methods.

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