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Proceedings Paper

Active visual computing model based on data- and knowledge-driven selective attention mechanism
Author(s): Fuhui Long; Nanning Zheng; David Dagan Feng
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Paper Abstract

Strong evidence has shown that visual processing based on selective attention is both data- and knowledge-driven. However, most of the previous work mainly focused on the former. We propose in this paper a new selective attention visual computing model based on both of them. The novelty lies in: (1) A structure variable non-uniform sampling method is proposed to separate visual computing into foveal and peripheral channel. (2) A combination of the bottom-up and the top-down selective attention mechanism based on a two-layered pyramid is proposed. The data-driven bottom-up selective attention includes the sequential extraction of feature maps, conspicuity maps, and interesting maps based on the multi-channel filtering and relaxation process. The knowledge driven top-down selective attention is based on distributed associative memory mapping. (3) A movement control mechanism is also proposed in this paper. Perfectly good experiment results on artificial and real times demonstrate the validity of our model.

Paper Details

Date Published: 19 May 1999
PDF: 12 pages
Proc. SPIE 3644, Human Vision and Electronic Imaging IV, (19 May 1999); doi: 10.1117/12.348469
Show Author Affiliations
Fuhui Long, Hong Kong Polytechnic Univ. (Hong Kong)
Nanning Zheng, Xi'an Jiaotong Univ. (China)
David Dagan Feng, Hong Kong Polytechnic Univ. (Hong Kong)


Published in SPIE Proceedings Vol. 3644:
Human Vision and Electronic Imaging IV
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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