Extraction and interpretation of semantically significant line segments for a mobile robot

Abstract

The authors describe algorithms for detecting and interpreting linear features of a real scene as images by a single camera on a mobile robot. The low-level processing stages were specifically designed to increase the usefulness and the quality of the extracted features for a semantic interpretation. The detection and interpretation processes provided a 3-D orientation hypothesis for each 2-D segment. This, in turn, was used to estimate the robot's orientation and relative position in the environment and to delimit the free space visible in the image. The orientation data was 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, an emphasis was placed on real-world applications and very fast processing with conventional hardware.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>