Coloring Channel Representations for Visual Tracking

  • Martin Danelljan
  • Gustav Häger
  • Fahad Shahbaz Khan
  • Michael Felsberg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9127)


Visual object tracking is a classical, but still open research problem in computer vision, with many real world applications. The problem is challenging due to several factors, such as illumination variation, occlusions, camera motion and appearance changes. Such problems can be alleviated by constructing robust, discriminative and computationally efficient visual features. Recently, biologically-inspired channel representations [9] have shown to provide promising results in many applications ranging from autonomous driving to visual tracking.

This paper investigates the problem of coloring channel representations for visual tracking. We evaluate two strategies, channel concatenation and channel product, to construct channel coded color representations. The proposed channel coded color representations are generic and can be used beyond tracking.

Experiments are performed on 41 challenging benchmark videos. Our experiments clearly suggest that a careful selection of color feature together with an optimal fusion strategy, significantly outperforms the standard luminance based channel representation. Finally, we show promising results compared to state-of-the-art tracking methods in the literature.


Visual tracking Channel coding Color names 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Martin Danelljan
    • 1
  • Gustav Häger
    • 1
  • Fahad Shahbaz Khan
    • 1
  • Michael Felsberg
    • 1
  1. 1.Computer Vision LaboratoryLinköping UniversityLinköpingSweden

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