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Proceedings Article

Computer vision for driver assistance systems

[+] Author Affiliations
Uwe Handmann, Thomas Kalinke, Christos Tzomakas, Martin Werner, Werner von Seelen

Ruhr-Univ. Bochum (Germany)

Proc. SPIE 3364, Enhanced and Synthetic Vision 1998, 136 (July 30, 1998); doi:10.1117/12.317463
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From Conference Volume 3364

  • Enhanced and Synthetic Vision 1998
  • Jacques G. Verly
  • Orlando, FL | April 13, 1998

abstract

Systems for automated image analysis are useful for a variety of tasks and their importance is still increasing due to technological advances and an increase of social acceptance. Especially in the field of driver assistance systems the progress in science has reached a level of high performance. Fully or partly autonomously guided vehicles, particularly for road-based traffic, pose high demands on the development of reliable algorithms due to the conditions imposed by natural environments. At the Institut fur Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We introduce a system which extracts the important information from an image taken by a CCD camera installed at the rear view mirror in a car. The approach consists of a sequential and a parallel sensor and information processing. Three main tasks namely the initial segmentation (object detection), the object tracking and the object classification are realized by integration in the sequential branch and by fusion in the parallel branch. The main gain of this approach is given by the integrative coupling of different algorithms providing partly redundant information.

© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Citation

Uwe Handmann ; Thomas Kalinke ; Christos Tzomakas ; Martin Werner and Werner von Seelen
"Computer vision for driver assistance systems", Proc. SPIE 3364, Enhanced and Synthetic Vision 1998, 136 (July 30, 1998); doi:10.1117/12.317463; http://dx.doi.org/10.1117/12.317463


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