Depth saliency based on anisotropic center-surround difference

Most previous works on saliency detection are dedicated to 2D images. Recently it has been shown that 3D visual information supplies a powerful cue for saliency analysis. In this paper, we propose a novel saliency method that works on depth images based on anisotropic center-surround difference. Ins...

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Bibliographic Details
Published inProceedings - International Conference on Image Processing pp. 1115 - 1119
Main Authors Ran Ju, Ling Ge, Wenjing Geng, Tongwei Ren, Gangshan Wu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2014
Subjects
Color
Computer vision
Conferences
depth image
Image edge detection
Pattern recognition
Saliency detection
Three-dimensional displays
Visualization
Online AccessGet full text
ISSN1522-4880
DOI10.1109/ICIP.2014.7025222

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Summary:Most previous works on saliency detection are dedicated to 2D images. Recently it has been shown that 3D visual information supplies a powerful cue for saliency analysis. In this paper, we propose a novel saliency method that works on depth images based on anisotropic center-surround difference. Instead of depending on absolute depth, we measure the saliency of a point by how much it outstands from surroundings, which takes the global depth structure into consideration. Besides, two common priors based on depth and location are used for refinement. The proposed method works within a complexity of O(N) and the evaluation on a dataset of over 1000 stereo images shows that our method outperforms state-of-the-art.
ISSN:1522-4880
DOI:10.1109/ICIP.2014.7025222