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Communication Dans Un Congrès Année : 2013

Saliency detection for stereoscopic images

Yuming Fang
Junle Wang
  • Fonction : Auteur
  • PersonId : 890939
Manish Narwaria
  • Fonction : Auteur
  • PersonId : 929210
IVC
Patrick Le Callet

Résumé

Saliency detection techniques have been widely used in various 2D multimedia processing applications. Currently, the emerging applications of stereoscopic display require new saliency detection models for stereoscopic images. Different from saliency detection for 2D images, depth features have to be taken into account in saliency detection for stereoscopic images. In this paper, we propose a new stereoscopic saliency detection framework based on the feature contrast of color, intensity, texture, and depth. Four types of features including color, luminance, texture, and depth are extracted from DC-T coefficients to represent the energy for image patches. A Gaussian model of the spatial distance between image patches is adopted for the consideration of local and global contrast calculation. A new fusion method is designed to combine the feature maps for computing the final saliency map for stereoscopic images. Experimental results on a recent eye tracking database show the superior performance of the proposed method over other existing ones in saliency estimation for 3D images.
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Dates et versions

hal-00932125 , version 1 (16-01-2014)

Identifiants

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Yuming Fang, Junle Wang, Manish Narwaria, Patrick Le Callet, Weisi Lin. Saliency detection for stereoscopic images. Visual Communications and Image Processing (VCIP), 2013, Nov 2013, kuching, Malaysia. pp.1--6, ⟨10.1109/VCIP.2013.6706346⟩. ⟨hal-00932125⟩
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