Graph-Based Perceptual Segmentation of Stereo Vision 3D Images at Multiple Abstraction Levels

This paper presents a new technique based on perceptual information for the robust segmentation of noisy 3D scenes acquired by stereo vision. A low-pass geometric ¯lter is ¯rst applied to the given cloud of 3D points to remove noise. The tensor voting algorithm is then applied in order to extract perceptual geometric information. Finally, a graph-based segmenter is utilized for extracting the di®erent geometric structures present in the scene through a region-growing procedure that is applied hierarchically. The proposed algorithm is evaluated on real 3D scenes acquired with a trinocular camera.