Biologically Motivated Face Selective Attention Model

In this paper, we propose a face selective attention model, which is based on biologically inspired visual selective attention for human faces. We consider the radial frequency information and skin color filter to localize a candidate region of human face, which is to reflect the roles of the V4 and the infero-temporal (IT) cells. The ellipse matching based on symmetry axis is applied to check whether the candidate region contain a face contour feature. Finally, face detection is conducted by face form perception model implemented by an auto-associative multi-layer perceptron (AAMLP) that mimics the roles of faces selective cells in IT area. Based on both the face-color preferable attention and face-form perception mechanism, the proposed model shows plausible performance for localizing face candidates in real time.

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