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When the human eye searches a natural scene, the left and right eyes converge on an interesting area by action of the brain and the eyeballs. This mechanism is based on two attention processes. In a top-down (or volitional) processing, the human visual system determines salient locations through perceptive processing such as understanding and recognition. On the other hand, with bottom-up (or image-based) processing, the human visual system determines salient locations obtained from features that are based on the basic information of an input image such as intensity, color, and orientation. Bottom-up processing is a function of primitive selective attention in the human vision system since humans selectively attend to a salient area according to various stimuli in the input scene (Itti et al., 1998). If we can apply the human-like vergence function considered human attention process to an active stereo vision system, an efficient and intelligent vision system can be developed. Researchers have been developing the vergence stereo system. It was known that the two major sensory drives for vergence and accommodation are disparity and blur (Krishnan & Stark, 1977; Hung & Semmlow, 1980). Krotkov organized the stereo system through waking up the camera, gross focusing, orienting the cameras, and obtaining depth information (Krotkov, 1987). Abbott and Ahuja proposed surface reconstruction by dynamic integration of the focus, camera vergence and stereo disparity (Abbott & Ahuja, 1988). These approaches give good results for a specific condition, but it is difficult to use these systems in real environment because the region extraction based on intensity information is very sensitive to luminance change. For mimicking a human vision system, Yamato implemented a layered control system for stereo vision head with vergence control function. This system utilized a search of the most similar region based on the sum of absolute difference (SAD) for tracking. The vergence module utilized a minimum SAD search for each pixel to obtain figure-ground separation in 3D space (Yamato, 1999). But these systems may not give good results when the camera is moving with background because the SAD contains much noise by moving the camera. Jian Peng et al. made that an active vision system enables the selective capture of information for a specific colored object

Biologically Motivated Vergence Control System Based on Stereo Saliency Map Model