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| A Visual Memory Model with Amnesic Function and Its Application in Attention Selection |
| GUO Chen-Lei, ZHANG Li-Ming |
| Department of Electronic Engineering, Fudan University, Shanghai 200433 |
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Abstract Based on the previous attention selection model with visual memory as top-down guidance, a visual memory model is put forward with online learning and forgetting, called amnesic incremental hierarchical discriminant regression (AIHDR) tree, to mimic human short-term memory (STM) and long-term memory (LTM). A self-supervised competition neural network (SSCNN) combines the information from both bottom-up and top-down to find out the focus of attention (FoA). The connection weights in SSCNN can be updated in real-time according to the environment. Experimental results show that the proposed model can mimic the shift of human attention and stare at an interesting object consciously when environment changes.
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Received: 09 April 2007
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2008, Vol. 21 
