Journal
IEEE TRANSACTIONS ON ROBOTICS
Volume 24, Issue 5, Pages 1015-1026Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2008.2004490
Keywords
Appearance; homography; omnidirectional camera; scale-invariant feature transform (SIFT) features; vehicle ego-motion estimation; visual odometry
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Funding
- European Commission Division FP6-IST Future and Emerging Technologies [FP6-IST-027140 (BACS)]
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In this paper, we describe a real-time algorithm for computing the ego-motion of a vehicle relative to the road. The algorithm uses as input only those images provided by a single omnidirectional camera mounted on the roof of the vehicle. The front ends of the system are two different trackers. The first one is a homography-based tracker that detects and matches robust scale-invariant features that most likely belong to the ground plane. The second one uses an appearance-based approach and gives high-resolution estimates of the rotation of the vehicle. This planar pose estimation method has been successfully applied to videos from an automotive platform. We give an example of camera trajectory estimated purely from omnidirectional images over a distance of 400 m. For performance evaluation, the estimated path is superimposed onto a satellite image. In the end, we use image mosaicing to obtain a textured 2-D reconstruction of the estimated path.
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