Stereo-vision based control of a car using fast line-segment extraction

Abstract

This paper describes our work on applying stereo vision to the control of a car or car-like mobile robot, using cheap, low-quality cameras. Our approach is based on line segments, since those provide significant information about the environment, provide more depth information than point features, and are robust to image noise and colour variation. However, stereo matching with line segments is a difficult problem, due to poorly localized end points and perspective distortion. Our algorithm uses integral images and Haar features for line segment extraction. Dynamic programming is used in the line segment matching phase. The resulting line segments track accurately from one frame to the next, even in the presence of noise. © 2009 Springer Berlin Heidelberg.