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Proceedings Paper

Obstacle detection for vehicle navigation by chaining of adoptive declivities using geometrical constrains
Author(s): Ravi Garg; Rajendra Sahu; Stéphane Mousset; Abdelaziz Bensrhair
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Paper Abstract

Here we present an approach of meaningful curve identification with its depth estimation by chaining of the edge points, to locate and track the obstacles with stereo matching for automatic vehicle navigation. We use a self adoptive and nonlinear principle of extended declivity to obtain the edge points (horizontal declivities) in the images. These edge points include lots of noise and hence matching is not effective directly. The large size of the matching problem does not allow us to use effective matching algorithm properly. We use basic assumptions of continuity in the shape of expected obstacles to reduce the problem size and match less number of features effectively. Vertical chaining is used to obtain features which can be used for the tracking or stereo and obtain obstacles in the region of interest. These newly proposed curves are defined with their features and a matching algorithm is used to obtain results.

Paper Details

Date Published: 26 February 2010
PDF: 7 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75461E (26 February 2010); doi: 10.1117/12.853483
Show Author Affiliations
Ravi Garg, Indian Institute of Information Technology and Management Gwalior (India)
Rajendra Sahu, Indian Institute of Information Technology and Management Gwalior (India)
Stéphane Mousset, INSA de Rouen (France)
Abdelaziz Bensrhair, INSA de Rouen (France)

Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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