Spherical Center-Surround for Video Saliency Detection Using Sparse Sampling

  • Hamed Rezazadegan Tavakoli
  • Esa Rahtu
  • Janne Heikkilä
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8192)


This paper presents a technique for detection of eminent (salient) regions in an image sequence. The method is inspired by the biological studies on human visual attention systems and is grounded on the famous center-surround theory. It hypothesis that an item (center) is dissimilar to its surrounding. A spherical representation is proposed to estimate amount of salience. It enables the method to integrate computation of temporal and spatial contrast features. Efficient computation of the proposed representation is made possible by sparse sampling the surround which result in an efficient spatiotemporal comparison. The method is evaluated against a recent benchmark methods and is shown to outperform all of them.


Independent Component Analysis Saliency Detection Visual Saliency Sparse Sampling Spherical Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hamed Rezazadegan Tavakoli
    • 1
  • Esa Rahtu
    • 1
  • Janne Heikkilä
    • 1
  1. 1.Center for Machine Vision ResearchUniversity of OuluFinland

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