Computer vision for driver assistance systems

  • 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.

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Metadaten
Author:Uwe Handmann, Thomas Kalinke, Christos Tzomakas, Martin Werner, Werner von Seelen
URL:https://www.spiedigitallibrary.org/conference-proceedings-of-spie/3364/1/Computer-vision-for-driver-assistance-systems/10.1117/12.317463.short?SSO=1
Parent Title (English):Proceedings of SPIE Vol. 3364, Session Enhanced and Synthetic Vision
Place of publication:Orlanda, USA
Document Type:Conference Proceeding
Language:English
Year of Completion:1998
Release Date:2019/07/09
Pagenumber:11
First Page:136
Last Page:147
Institutes:Fachbereich 1 - Institut Informatik
DDC class:000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):License LogoNo Creative Commons