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Online Visual Tracking Using Temporally Coherent Part Clusters

This paper introduces a reliable target representation composed of local parts for online visual tracking, addressing the challenges of occlusions and deformations.

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Online Visual Tracking Using Temporally Coherent Part Clusters

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  1. Online Visual Tracking Using Temporally Coherent Part Clusters Wenbo Li*, Longyin Wen†, Mooi Choo Chuah*, Yi Zhang‡, Zhen Lei†, Stan Z. Li† *Department of Computer Science and Engineering, Lehigh University, †National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, ‡School of Computer Software, Tianjin University

  2. Background Occlusion Deformation How can we come up with a reliable target representation using local parts? Part-based Appearance Model 1/5

  3. Motivation • Few current existing tracking algorithms perform well in the presence of occlusions and deformations. • In this paper, we aim to address these two issues by using a reliable target representation composed of local parts. 2/5

  4. Spotlight We propose a reliable target representation: Temporally Coherent Part (TCP). • The definition of TCP: within a temporal span, if there are multiple local parts that have similar appearances and similar motion patterns, these local parts can form one temporal cluster and each of these local parts is considered as a TCP. • TCPs are determined by identifying TCP clusters. 3/5

  5. Overall Approach Figure 1. Overall tracking procedure for one video segment. The green rectangle and the blue dotted rectangle represent the search window and the sample window respectively. The green colored local parts are in the Candidate Target Part Set. Target parts within a TCP cluster are colored the same in the Final Target Part Set. 4/5

  6. Thank you! Please email questions to:wbli@lehigh.edu 5/5

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