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Vehicle Detection by means of Stereo Vision-based Obstacles Features Extraction and Monocular Pattern Analysis

Abstract : This paper presents a stereo vision system for the detection and distance computation of a preceding vehicle. It is divided in two major steps. Initially, a stereo vision based algorithm is used to extract relevant 3D features in the scene, these features are investigated further in order to select the ones that belong to vertical objects only and not to the road or background. These 3D vertical features are then used as a starting point for preceding vehicle detection; by using a symmetry operator, a match against a simplified model of a rear vehicle's shape is performed using a monocular vision-based approach that allows the identification of a preceding vehicle. In addition, using the 3D information previously extracted, an accurate distance computation is performed.
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https://hal.archives-ouvertes.fr/hal-00478467
Contributor : Stéphane Mousset <>
Submitted on : Friday, April 30, 2010 - 2:46:38 PM
Last modification on : Tuesday, July 23, 2019 - 4:04:10 PM

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  • HAL Id : hal-00478467, version 1

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Gwénaëlle Toulminet, M. Bertozzi, Stéphane Mousset, Alberto Broggi, Abdelaziz Bensrhair. Vehicle Detection by means of Stereo Vision-based Obstacles Features Extraction and Monocular Pattern Analysis. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2006, 15 (8), pp.2364-2375. ⟨hal-00478467⟩

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