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Abstract
This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object detection is based on motion analysis of individually tracked image points (optical flow), providing a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric, points are segmented into objects by employing a globally optimal graph-cut algorithm. Both approaches are comparatively evaluated using real-world vehicle image sequences.
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Published on 01/01/2009
Volume 2009, 2009
DOI: 10.1007/978-3-540-92957-4_53
Licence: CC BY-NC-SA license
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