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Correcting Vehicle Heading in Visual Odometry by Using Image Appearance

This paper describes a visual odometry algorithm for onroad vehicles under planar motion assumption. The algorithm uses as only input images taken by a single omnidirectional camera mounted on the roof of the vehicle. To achieve accurate motion estimation results, we decouple the rotation and translation estimation. In particular, we use a feature based ground plane tracker to estimate the translation and an appearance based method to estimate the rotation. As we show, the use of image appearance to estimate the vehicle heading outperforms the pure feature based approach. This 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.