Title :
Visual saliency based on natural scene statistics
Author :
Tiantian Lou ; Jinhua Xu
Author_Institution :
Dept. of Comput. Sci. & Technol., East China Normal Univ., Shanghai, China
Abstract :
Visual saliency is the perceptual quality that makes some items in visual scenes stand out from their immediate contexts. According to the center-surround hypothesis of saliency, it is commonly assumed that bottom-up saliency is determined by how distinct the stimulus (features) at each location of the visual field is from the stimuli (features) in its surround. Using the center-surround configuration from different scales, we define the saliency measure based on the conditional probability of the center given the surround, which is obtained from natural scene statistics (collected from a large set of images of natural scenes). It is demonstrated that the proposed model of visual saliency predicts well human gaze in free viewing static natural scenes.
Keywords :
computer vision; probability; bottom-up saliency; center-surround configuration; conditional probability; human gaze; natural scene statistics; saliency measurement; visual saliency; Computational modeling; Context; Context modeling; Histograms; Humans; Predictive models; Visualization; natural scene statistics; visual attention; visual saliency;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022196