Volume 6 Number 9 (Sep. 2011)
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JSW 2011 Vol.6(9): 1705-1712 ISSN: 1796-217X
doi: 10.4304/jsw.6.9.1705-1712

A Hierarchical Computational Model of Selective Visual Attention

Qiaorong Zhang1, Huimin Xiao2, Haibo Liu3
1College of Computer and Information Engineering, Henan University of Finance and Economics, Zhengzhou, China
2Department of Mathematics and Information, Henan University of Finance and Economics, Zhengzhou, China
3College of Computer Science and Technology, Harbin Engineering University, Harbin, China

Abstract—Computational model of visual attention has got more and more attention in machine vision and image processing. A hierarchical computational model for selective visual attention is proposed in this paper. This model simulates the attention mechanism from far (coarse) to near (fine) of human visual system. Firstly, the input image is analyzed at the coarsest resolution and visual saliency of each part is computed at this level. Regions of attention are selected according to the saliency. Then the sub-regions of the selected region compete for attention at a finer resolution. This process is done iteratively until every salient region and its sub-regions have been processed at different levels respectively. The proposed model has been tested on many natural images. Experiment results show that the proposed model is valid and the attention results are consistent with human visual system.

Index Terms—visual attention, image processing, visual saliency, saliency map, hierarchical selection


Cite: Qiaorong Zhang, Huimin Xiao, Haibo Liu, "A Hierarchical Computational Model of Selective Visual Attention," Journal of Software vol. 6, no. 9, pp. 1705-1712, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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