Salient region detection using weighted feature maps based on the human visual attention model

  • Authors:

  • Yiqun Hu;Xing Xie;Wei-Ying Ma;Liang-Tien Chia;Deepu Rajan

  • Affiliations:

  • Center for Multimedia and Network Technology, School of Computer Engineering, Nanyang Technological University, Singapore;Microsoft Research Asia, P.R. China;Microsoft Research Asia, P.R. China;Center for Multimedia and Network Technology, School of Computer Engineering, Nanyang Technological University, Singapore;Center for Multimedia and Network Technology, School of Computer Engineering, Nanyang Technological University, Singapore

  • Venue:
  • PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
  • Year:
  • 2004

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Abstract

Detection of salient regions in images is useful for object based image retrieval and browsing applications. This task can be done using methods based on the human visual attention model [1], where feature maps corresponding to color, intensity and orientation capture the corresponding salient regions. In this paper, we propose a strategy for combining the salient regions from the individual feature maps based on a new Composite Saliency Indicator (CSI) which measures the contribution of each feature map to saliency. The method also carries out a dynamic weighting of individual feature maps. The experiment results indicate that this combination strategy reflects the salient regions in an image more accurately.