Vision-based road detection in automotive systems: a real-time expectation-driven approach

  • Authors:
  • Alberto Broggi;Simona Berté

  • Affiliations:
  • Dipartimento di Ingegneria dell'Informazione, Universitá di Parma, Parma, Italy;Dipartimento di Ingegneria dell'Informazione, Universitái Parma, Parma, Italy

  • Venue:
  • Journal of Artificial Intelligence Research
  • Year:
  • 1995

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Abstract

The main aim of this work is the development of a vision-based road detection system fast enough to cope with the difficult real-time constraints imposed by moving vehicle applications. The hardware platform, a special-purpose massively parallel system, has been chosen to minimize system production and operational costs. This paper presents a novel approach to expectation-driven low-level image segmentation, which can be mapped naturally onto mesh-connected massively parallel Simd architectures capable of handling hierarchical data structures. The input image is assumed to contain a distorted version of a given template; a multiresolution stretching process is used to reshape the original template in accordance with the acquired image content, minimizing a potential function. The distorted template is the process output.