Patch-based object tracking via Locality-constrained Linear Coding

Kunqi Gu, Mingna Liu, Tao Zhou, Fanghui Liu, Xiangjian He, Jie Yang, Yu Qiao

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)


In this paper, the Locality-constrained Linear Coding(LLC) algorithm is incorporated into the object tracking framework. Firstly, we extract local patches within a candidate and then utilize the LLC algorithm to encode these patches. Based on these codes, we exploit pyramid max pooling strategy to generate a richer feature histogram. The feature histogram which integrates holistic and part-based features can be more discriminative and representative. Besides, an occlusion handling strategy is utilized to make our tracker more robust. Finally, an efficient graph-based manifold ranking algorithm is exploited to capture the relevance between target templates and candidates. For tracking, target templates are taken as labeled nodes while target candidates are taken as unlabeled nodes, and the goal of tracking is to search for the candidate that is the most relevant to existing labeled nodes by manifold ranking algorithm. Experiments on challenging video sequences have demonstrated the superior accuracy and robustness of the proposed method in comparison to other state-of-the-art baselines.

Original languageEnglish
Title of host publicationProceedings of the 35th Chinese Control Conference, CCC 2016
EditorsJie Chen, Qianchuan Zhao, Jie Chen
PublisherIEEE Computer Society
Number of pages6
ISBN (Electronic)9789881563910
Publication statusPublished - 26 Aug 2016
Externally publishedYes
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: 27 Jul 201629 Jul 2016

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927


Conference35th Chinese Control Conference, CCC 2016


  • LLC
  • local appearance model
  • manifold ranking
  • object tracking
  • pyramid max-pooling

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modelling and Simulation


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