This paper is concerned with the problem of estimating the motion of a single camera from a sequence of images, with an application scenario of vehicle egomotion estimation. Egomotion estimation has been an active area of research for many years and various solutions to the problem have been proposed. Many methods rely on optical flow or local image features to establish the spatial relationship between two images. A new method of egomotion estimation is presented which makes use of the Fourier-Mellin Transform for registering images in a video sequence, from which the rotation and translation of the camera motion can be estimated. The Fourier-Mellin Transform provides an accurate and efficient way of computing the camera motion parameters. It is a global method that takes the contributions from all pixels into account. The performance of the proposed approach is compared to two variants of optical flow methods and results are presented for a real-world video sequence taken from a moving vehicle.
Visual Vehicle Egomotion Estimation using the Fourier-Mellin Transform
2007 IEEE Intelligent Vehicles Symposium ; 450-455
2007-06-01
733827 byte
Conference paper
Electronic Resource
English
Visual Vehicle Egomotion Estimation Using the Fourier-Mellin Transform
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