Biologically Inspired Selective Attention Model Using Human Interest
نویسندگان
چکیده
A new selective attention model is proposed in this paper, which integrates a top-down attention mechanism into a bottom-up saliency map model to generate salient areas related with human interest. Human selects the certain area from natural scene and decides whether the selected area is preference or refusal. The fuzzy adaptive resonance theory (ART) network trains and memorizes the characteristic of that area, also generates a refusal or a preference signal so that the sequence of test areas is modified to be a desired scan path. The proposed model generates a plausible scan path based on human interest by endowing weight values to feature maps in a course of constructing the saliency map. Keyword: Knowledge representation, selective attention model, autonomous mental development, self organizing feature map, adaptive resonance theory network
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