Biologically Motivated Face Selective Attention System

In this paper, we propose a biologically motivated face preference selective attention system to identify a face within complex natural scenes. In order to localize a face in natural scenes, we have developed a task-specific selective attention model which integrates the conventional bottom-up saliency map with punishment and rewarding functions, with top-down attention and bias signals, according to a given task. The color-filtered intensity, color opponent, and edge of the winner color opponent features are intensified for the biasing of skin color in order to identify a face. Computer experimental results have shown that the proposed model successfully identifies multiple faces within a complex environment. In addition, we have implemented a robot vision system which will be used for an autonomous mental development system.