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Independent Motion Segmentation and Collision Prediction for Road Vehicles

David Sinclair 1 Boubakeur Boufama 1, 2 
2 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : This paper presents a method for doing motion segmentation for autonomous vehicles which drive on planar surfaces. There are two distinct types of independent motion that may occur within an image sequence taken from a moving vehicle. The first generic type of independent motion is when the projected motion of points on the independent object violate the epipolar constraint. The second case is where the epipolar constraint is not violated. This paper demonstrates that it is possible to detect this second type of independent motion by looking for progressive dis-occlusion of the road. A novel collision prediction method is also given. The method predicts the projection of a corridor down which the AGV will travel. This prediction may be used for time to contact collision prediction and the corridor width embodies an estimate of the vehicles size.
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Submitted on : Tuesday, May 3, 2011 - 9:10:12 AM
Last modification on : Friday, February 4, 2022 - 3:32:05 AM

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David Sinclair, Boubakeur Boufama. Independent Motion Segmentation and Collision Prediction for Road Vehicles. 3rd European Conference on Computer Vision (ECCV '94), May 1994, Stockholm, Sweden. pp.161--166, ⟨10.1007/3-540-57956-7_18⟩. ⟨inria-00590033⟩



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