RECURSIVE SURFACE STRUCTURE RECOGNITION FOR SAFE NAVIGATION

In this paper, a general formulation for a 3-D surface structure recognition is given. The superimposed geometrical models introduced make it possible to estimate the surface structure separated into different spatial frequencies. This technique has been developed in order to efficiently cover all navigational aspects from hilly terrain to the detection of small obstacles.

• Supplemental Notes:
  • Publication Date: 1995 Published By: IEEE Service Center, Piscataway NJ
• Corporate Authors:

  Universitat der Bundeswehr Munchen

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  Ohio State University, Columbus

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  Johns Hopkins University, Laurel

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  University of Washington, Seattle

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  Texas A&M University, College Station

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  Universite Paris-Sud. Institut d'electronique fondamentale

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  Ruhr-Universitat Bochum. Institut fur Neuroinformatik

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  GERMANY. BUNDESSTELLE FSUR FLUGUNFALL-UNTERSUCHUNG

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  Bayerische Motoren Werke

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  Daimler-Benz A.G.

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  Prometheus (Program)

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  Carnegie Mellon University

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  University of California, Berkeley

  California PATH Program, Institute of Transportation Studies
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• Authors:
  • Baten, Stefan
• Conference:
  • Intelligent Vehicles '95 Symposium (1995 : Detroit, Mich.). Proceedings of the Intelligent Vehicles '95 Symposium
• Publication Date: 1995

Language

• English

Media Info

• Pagination: p. 424-429

Subject/Index Terms

• TRT Terms: Pattern recognition systems

Filing Info

• Accession Number: 00787456
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH, STATEDOT
• Created Date: Nov 17 2000 12:00AM