
Proceedings Paper
Distributed Scene Analysis For Autonomous Road Vehicle GuidanceFormat | Member Price | Non-Member Price |
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Paper Abstract
An efficient distributed processing scheme has been developed for visual road boundary tracking by 'VaMoRs', a testbed vehicle for autonomous mobility and computer vision. Ongoing work described here is directed to improving the robustness of the road boundary detection process in the presence of shadows, ill-defined edges and other disturbing real world effects. The system structure and the techniques applied for real-time scene analysis are presented along with experimental results. All subfunctions of road boundary detection for vehicle guidance, such as edge extraction, feature aggregation and camera pointing control, are executed in parallel by an onboard multiprocessor system. On the image processing level local oriented edge extraction is performed in multiple 'windows', tighly controlled from a hierarchically higher, modelbased level. The interpretation process involving a geometric road model and the observer's relative position to the road boundaries is capable of coping with ambiguity in measurement data. By using only selected measurements to update the model parameters even high noise levels can be dealt with and misleading edges be rejected.
Paper Details
Date Published: 1 January 1987
PDF: 8 pages
Proc. SPIE 0852, Mobile Robots II, (1 January 1987); doi: 10.1117/12.968237
Published in SPIE Proceedings Vol. 0852:
Mobile Robots II
Wendell H. Chun; William J. Wolfe, Editor(s)
PDF: 8 pages
Proc. SPIE 0852, Mobile Robots II, (1 January 1987); doi: 10.1117/12.968237
Show Author Affiliations
Birger D. Mysliwetz, Universitat der Bundeswehr Munchen (West Germany)
E. D. Dickmanns, Universitat der Bundeswehr Munchen (West Germany)
Published in SPIE Proceedings Vol. 0852:
Mobile Robots II
Wendell H. Chun; William J. Wolfe, Editor(s)
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