Robust Visual Odometry for Complex Urban Environments

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Title Robust Visual Odometry for Complex Urban Environments
Author Parra, Ignacio; Sotelo, Miguel Angel; Vlacic, Ljubo (Ljubisa)
Publication Title Proceedings of the IEEE Intelligent Vehicles Symposium - IV08
Editor Henk Nijmeijer and Bart van Arem
Year Published 2008
Place of publication Eindhoven, The Netherlands
Publisher IEEE, Eindhoven University of Technology
Abstract This paper describes a new approach for estimating the vehicle motion trajectory in complex urban environments by means of visual odometry. A new strategy for robust feature extraction and data post-processing is developed and tested on-road. Scale-invariant Image Features (SIFT) are used in order to cope with the complexity of urban environments. The obtained results are discussed and compared to previous works. In the prototype system, the ego-motion of the vehicle is computed using a stereo-vision system mounted next to the rear view mirror of the car. Feature points are matched between pairs of frames and linked into 3D trajectories. The distance between estimations is dynamically adapted based on reprojection and estimation errors. Vehicle motion is estimated using the non-linear, photogrametric approach based on RANSAC (RAndom SAmple Consensus). The obvious application of the method is to provide on-board driver assistance in navigation tasks, or to provide a means of autonomously navigating a vehicle. The method has been tested in real traffic conditions without using prior knowledge about the scene or the vehicle motion. An example of how to estimate a vehiclepsilas trajectory is provided along with suggestions for possible further improvement of the proposed odometry algorithm.
Peer Reviewed Yes
Published Yes
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Copyright Statement Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 978-1-4244-2569-6
Conference name IV08 Intelligent Vehicles Symposium
Location Eindhoven, The netherlands
Date From 2008-06-04
Date To 2008-06-06
Date Accessioned 2009-05-07
Language en_AU
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Control Systems, Robotics and Automation
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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