Geometrical Modeling from Multiple Stereo Views

Abstract

The components of the Sheffield Artificial Intelligence Vision Research Unit (AIVRU) three-dimensional (3D) vision sys tem, which currently supports model-based object recognition and location, are described. Its potential for robotics applica tions is demonstrated by its guidance of a Universal Machine Intelligence robot arm in a pick-and-place task. The system comprises (1) the recovery of a sparse depth map using edge- based, passive stereo triangulation; (2) the grouping, descrip tion, and segmentation of edge segments to recover a 3D representation of the scene geometry in terms of straight lines and circular arcs; (3) the statistical combination of 3D de scriptions for object model creation from multiple stereo views and the propagation of constraints for within-view re finement ; and (4) the matching of 3D wireframe object models to 3D scene descriptions in order to recover an initial estimate of their position and orientation.