The authors describe an exploratory vergence method which has the ability to detect occlusion and specular highlights using information that is inherent in the vergence process. They propose an active exploratory vergence method based on concurrent cross-correlation of multi-scale stereo images. This method is capable of detecting occlusion and specular highlights concurrently during the vergence process. It not only improves computational efficiency but also leads to the exploration of a better viewing direction and position that overcome the problem created by occlusion and specular highlights. An efficient parallel implementation of the multi-scale cross-correlation algorithm is also described. The robustness of the proposed method against occlusion and specular highlights is demonstrated.>

The authors show that occlusion can be detected by early visual processes derived directly from the image data. Two methods are demonstrated. The first method is based on detecting binocular rivalry during binocular fixation. The feasibility of this technique also supports the hypothesis that stereo fusion and rivalry coexist in human vision. Stereo fusion gives rise to smooth disparity whereas rivalry signals depth discontinuity. The second method uses focal information that results from a change in depth of field. This method does not involve changes of viewpoint and hence avoids the correspondence problem. These two methods together with cues from motion, as has been suggested elsewhere, form robust occlusion detection in early visual processing.>