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	Measuring Visual Saliency by Site Entropy Rate
	Wang, Wei ; Wang, Yizhou ; Huang, Qingming ; Gao, Wen
	2010
英文摘要	In this paper, we propose a new computational model for visual saliency derived from the information maximization principle. The model is inspired by a few well acknowledged biological facts. To compute the saliency spots of an image, the model first extracts a number of sub-band feature maps using learned sparse codes. It adopts a fully-connected graph representation for each feature map, and runs random walks on the graphs to simulate the signal/information transmission among the interconnected neurons. We propose a new visual saliency measure called Site Entropy Rate (SER) to compute the average information transmitted from anode (neuron) to all the others during the random walk on the graphs/network. This saliency definition also explains the center-surround mechanism from computation aspect. We further extend our model to spatial-temporal domain so as to detect salient spots in videos. To evaluate the proposed model, we do extensive experiments on psychological stimuli, two well known image datasets, as well as a public video dataset. The experiments demonstrate encouraging results that the proposed model achieves the state-of-the-art performance of saliency detection in both still images and videos.; Computer Science, Artificial Intelligence; Computer Science, Software Engineering; Mathematics, Applied; Imaging Science & Photographic Technology; EI; CPCI-S(ISTP); 46
语种	英语
DOI标识	10.1109/CVPR.2010.5539927
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/406180]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Wang, Wei,Wang, Yizhou,Huang, Qingming,et al. Measuring Visual Saliency by Site Entropy Rate. 2010-01-01.

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