Stereo vision of a mobile robot: World constraints for image matching and interpretation

Abstract

Stereo images taken by a mobile robot are analyzed and integrated into a world model. The knowledge on the properties of the environment, such as the flatness of floor and the richness in vertical surfaces, is arranged into constraints on matching and interpreting images. First, the stereo matcher detects edge points on the floor by predicting disparities from a camera model and testing them in actual images. Next, the correspondences of vertical edges starting at the floor edge points are established. By iterating similar procedures, vertical edges starting from edge points at different levels in scene are also detected. The hypothesis that a region between two vertical edges in scene is a vertical planar surface is proposed and tested by examining whether the disparities predicted from the 3-D geometry of the hypothesized surface contradict with those of patterns appeared in the region.