Salient Object Segmentation Based on Automatic Labeling

  • Lei Zhou
  • Chen Gong
  • YiJun Li
  • Yu Qiao
  • Jie Yang
  • Nikola Kasabov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8228)

Abstract

This paper proposes an automatic salient object extraction framework. Firstly, the saliency model are developed by applying the low level color features and the boundary prior. The initial salient regions are extracted by adaptive thresholding. Multiple classifiers are trained with extracted initial region, which reflect color information of images or adopt label propagation. Then, the labels for segmentation are generated automatically via classifier composition. Finally, the conditional random field (CRF) model based on multi-feature fusion is applied for salient object segmentation. Empirical study reveals that the proposed algorithm achieves satisfying performance.

Keywords

saliency detection automatic object segmentation automatic labeling conditional random field 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lei Zhou
    • 1
  • Chen Gong
    • 1
  • YiJun Li
    • 1
  • Yu Qiao
    • 1
  • Jie Yang
    • 1
  • Nikola Kasabov
    • 2
  1. 1.Institute of Image Processing and Pattern RecognitionShanghai Jiaotong UniversityChina
  2. 2.Auckland University of TechnologyNew Zealand

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