Significant line segments for an indoor mobile robot

Abstract

New algorithms for detecting and interpreting linear features of a real scene as imaged by a single camera on a mobile robot are described. The low-level processing stages are specifically designed to increase the usefulness and the quality of the extracted features for indoor scene understanding. In order to derive 3-D information from a 2-D image, we consider only lines with particular orientation in 3-D. The detection and interpretation processes provide a 3-D orientation hypothesis for each 2-D segment. This in turn is used to estimate the robot's orientation and relative position in the environment. Next, the orientation data is used by a motion stereo algorithm to fully estimate the 3-D structure when a sequence of images becomes available. From detection to 3-D estimation, a strong emphasis is placed on real-world applications and very fast processing with conventional hardware. Results of experimentation with a mobile robot under realistic conditions are given and discussed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>