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Saliency Density Maximization for Object Detection and Localization

  • Ye Luo
  • Junsong Yuan
  • Ping Xue
  • Qi Tian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6494)

Abstract

Accurate localization of the salient object from an image is a difficult problem when the saliency map is noisy and incomplete. A fast approach to detect salient objects from images is proposed in this paper. To well balance the size of the object and the saliency it contains, the salient object detection is first formulated with the maximum saliency density on the saliency map. To obtain the global optimal solution, a branch-and-bound search algorithm is developed to speed up the detection process. Without any prior knowledge provided, the proposed method can effectively and efficiently detect salient objects from images. Extensive results on different types of saliency maps with a public dataset of five thousand images show the advantages of our approach as compared to some state-of-the-art methods.

Keywords

Exhaustive Search Object Detection Salient Object Salient Region Saliency Detection 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ye Luo
    • 1
  • Junsong Yuan
    • 1
  • Ping Xue
    • 1
  • Qi Tian
    • 2
  1. 1.School of EEENanyang Technological UniversitySingapore
  2. 2.Institute for Infocomm ResearchSingapore

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