Monocular omnidirectional visual odometry for outdoor ground vehicles

This paper describes an algorithm for visually computing the ego-motion of a vehicle relative to the road under the assumption of planar motion. The algorithm uses only images taken 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 2D 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 meters. For performance evaluation, the estimated path is superimposed onto an aerial image. In the end, we use image mosaicing to obtain a textured 2D reconstruction of the estimated path.

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