Fourier Mellin transform characterisation in the automotive environment

Abstract

This paper discusses the problem of reliably estimating motion in video sequences. A core issue in this application is the registration of successive images in an image sequence of a dynamic scene. The paper examines the core characteristics of the Fourier Mellin transform (FMT) when applied to this task in the automotive environment. Of particular interest are the transformational, scale and rotational invariances of the transform. The objective of the paper is to examine the behaviour of the algorithm under wide variations in these three parameters. Images from a range of automotive scenarios are considered in this evaluation. Our main contributions are the experimental evaluations carried out on various images with a range of known translations, rotations and scale changes. The results of the experimental process allow the determination of the relationship between the transformation of image patches, and the resulting level of error in motion estimation. This helps to inform the application of the FMT, when it is effective, and where its limitations occur. The results of the experimental process described in this paper may be applied in several ways in practice. The applicability of the method may be extended through the addition of environmental variables from external sensors, i.e. CAN bus data, GPS or spatial feature ego-motion. This allows adaptive execution of the transform.