Motion Estimation using Tangent Distance

In this paper, we present a method based on tangent distance to estimate motion in image sequences. Tangent distance combines an intuitive understanding and effective modeling of differences between patterns. This tool was first introduced and successfully applied in character recognition. It allows to compare patterns according to small transformations (translations, rotations, etc.). We show, how to take advantages of some properties of tangent distances to perform a robust motion estimation algorithm. Particularly, the presented algorithm can easily be adapted and optimized to various types of movements and can also be used to estimate optical flow in image sequences. Moreover, and despite a time of computation a bit long, this algorithm can be massively paralleled.