Salient region detection based on binocular vision
Zhong Liu, Weihai Chen, Yuhua Zou, Xingming Wu · 2012
Selective visual attention is a kind of mechanism of the primate visual system for rapidly focusing on attractive objects or regions in visual environment. Numerous visual attention models have been developed and optimized over the past decades. Most of the existing models concentrate on static monocular image, but little attention has been devoted to stereo depth information which is an important aspect of human perception. A region-based binocular saliency detection approach considering depth information is proposed in this paper. The difference of left and right image is used for computing disparity map and coarse saliency map. Hue, saturation, and intensity (HSI) color space is adopted and mean-shift algorithm is used for image segmentation. This study shows that the proposed region-based saliency computational method can effectively detect salient region, and it is more suitable for real time applications such as obstacle detection and visual navigation for its simplicity.