Active visual computing model based on data- and knowledge-driven selective attention mechanism

Fuhui Long; Nanning Zheng; David Dagan Feng

doi:10.1117/12.348469

19 May 1999 Active visual computing model based on data- and knowledge-driven selective attention mechanism

Fuhui Long, Nanning Zheng, David Dagan Feng

Proceedings Volume 3644, Human Vision and Electronic Imaging IV; (1999) https://doi.org/10.1117/12.348469
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

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.

Citation Download Citation

Fuhui Long, Nanning Zheng, and David Dagan Feng "Active visual computing model based on data- and knowledge-driven selective attention mechanism", Proc. SPIE 3644, Human Vision and Electronic Imaging IV, (19 May 1999); https://doi.org/10.1117/12.348469

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