A Visual Saliency Map Based on Random Sub-window Means

  • Tadmeri Narayan Vikram
  • Marko Tscherepanow
  • Britta Wrede
Conference paper

DOI: 10.1007/978-3-642-21257-4_5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6669)
Cite this paper as:
Narayan Vikram T., Tscherepanow M., Wrede B. (2011) A Visual Saliency Map Based on Random Sub-window Means. In: Vitrià J., Sanches J.M., Hernández M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg

Abstract

In this article, we propose a simple and efficient method for computing an image saliency map, which performs well on both salient region detection and as well as eye gaze prediction tasks. A large number of distinct sub-windows with random co-ordinates and scales are generated over an image. The saliency descriptor of a pixel within a random sub-window is given by the absolute difference of its intensity value to the mean intensity of the sub-window. The final saliency value of a given pixel is obtained as the sum of all saliency descriptors corresponding to this pixel. Any given pixel can be included by one or more random sub-windows. The recall-precision performance of the proposed saliency map is comparable to other existing saliency maps for the task of salient region detection. It also achieves state-of-the-art performance for the task of eye gaze prediction in terms of receiver operating characteristics.

Keywords

Bottom-up Visual Attention Saliency Map Salient Region Detection Eye Fixation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tadmeri Narayan Vikram
    • 1
    • 2
  • Marko Tscherepanow
    • 1
  • Britta Wrede
    • 1
    • 2
  1. 1.Applied Informatics GroupBielefeld UniversityBielefeldGermany
  2. 2.Research Institute for Cognition and Robotics (CoR-Lab)Bielefeld UniversityBielefeldGermany

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