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Stereovision-based 3D obstacle detection for automotive safety driving assistance

Abstract : This paper describes the implementation of a real-time architecture dedicated to obstacle detection in the automotive domain, and more particularly to pre-crash situations. The method, based on stereovision, is of high complexity and can not run in real-time on standard processors. Therefore, the application is accelerated with the use of special purpose hardware; in particular, a highly parallelized disparity engine is presented. A prototype board was built, which achieves a performance of 460 GOPS and computes the application at the rate of 22 frames per second, thus reaching road safety constraints.
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Contributor : Nicolas Ventroux Connect in order to contact the contributor
Submitted on : Friday, July 24, 2009 - 5:28:32 PM
Last modification on : Thursday, February 17, 2022 - 10:08:03 AM


  • HAL Id : cea-00407474, version 1




Nicolas Ventroux, Renaud Schmit, Frédéric Pasquet, Pierre-Emmanuel Viel, Stéphane Guyetant. Stereovision-based 3D obstacle detection for automotive safety driving assistance. 12th International IEEE Conference on Intelligent Transportation Systems, Oct 2009, Saint-Louis, United States. ⟨cea-00407474⟩



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