In Proceedings

Robust visual odometry for complex urban environments

Parra, Ignacio; Sotelo, Miguel Ángel; Vlacic, L.
Year: 2008
Type of Publication: In Proceedings
Keywords: complex urban environment; ego-motion; feature extraction; onboard driver assistance; photogrametric approach; random sample consensus; robust visual odometry; scale-invariant image feature; stereo-vision system; vehicle motion trajectory; distance measurement; feat
Book title: Intelligent Vehicles Symposium, 2008 IEEE
Pages: 440 -445
Month: june
ISSN: 1931-0587
DOI: 10.1109/IVS.2008.4621277
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.
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