Local Binary Pattern as a Texture Feature Descriptor in Object Tracking Algorithm

  • Prajna Parimita Dash
  • Dipti Patra
  • Sudhansu Kumar Mishra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 243)


In this paper, we address a real-time object tracking algorithm considering local binary pattern (LBP) as a feature descriptor. In addition to texture feature, Ohta color features are included in the feature vector of the covariance tracking algorithm. The performance of the proposed algorithm is compared with some other competitive object tracking algorithms such as the RGB feature-based covariance method and color histogram method. The comparisons of the performance among these algorithms include detection rate and computational time. These methods have been applied to four different challenging situations, and the resulting experimental results show the robustness of the proposed technique against occlusion, camera motion, appearance, and change in illumination condition.


Object tracking Covariance matrix Local binary pattern Riemannian geometry 


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Copyright information

© Springer India 2014

Authors and Affiliations

  • Prajna Parimita Dash
    • 1
  • Dipti Patra
    • 1
  • Sudhansu Kumar Mishra
    • 2
  1. 1.IPCV LabNational Institute of TechnologyRourkelaIndia
  2. 2.Birla Institute of TechnologyRanchiIndia

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