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Robust Obstacle Detection based on Dense Disparity Maps

Abstract : Obstacle detection is an important component for many autonomous vehicle navigation systems. Several methods for obstacle detection have been proposed using various active sensors such as radar, sonar and laser range finders. Vision based techniques have the advantage of low cost and provide a large amount of information about the environment around an intelligent vehicle. This paper deals with the development of an accurate and efficient vision based obstacle detection method which relies on a wavelet analysis. The development system will be integrated on the Cybercar platform which is a road vehicle with fully automated driving capabilities.
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Submitted on : Thursday, February 8, 2007 - 4:13:51 PM
Last modification on : Thursday, January 20, 2022 - 5:29:53 PM
Long-term archiving on: : Friday, September 21, 2012 - 11:14:07 AM


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  • HAL Id : inria-00129750, version 1


Wided Miled, Jean-Christophe Pesquet, Michel Parent. Robust Obstacle Detection based on Dense Disparity Maps. Eleventh International Conference on Computer Aided Systems Theory - EUROCAST 2007, Feb 2007, Las Palmas de Gran Canaria, Canary Islands / Espagne. ⟨inria-00129750⟩



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