Abstract
Recently, dense disparity map is employed in many researches of real environmental recognition. Semi-Global Matching is one of the calculation techniques for a dense disparity map. This technique calculates disparities based on minimization of matching costs and disparity variations. However, some invalid disparities sometimes are included in the dense disparity map. They are obtained in the position which connects objects, and will harm to the object detection and the estimation of its size. In this manuscript, we propose an invalid disparity detection technique using DBSCAN. This technique is confirmed that can detect invalid disparities in experiment using real environmental scene.
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