Motion Determination in Space-Time Images

Abstract

A new approach to determine motion from multiple images of a sequence is presented. Motion is regarded as orientation in a three-dimensional space with one time and two space coordinates. The algorithm is analogous to an eigenvalue analysis of the inertia tensor. Besides the determination of the displacement vector field it allows the classification of four regions with regard to motion: a) constant regions, where no velocity determination is possible; b) edges, where the velocity component perpendicular to the edge is determined; c) corners, where both components of the velocity vector are calculated; d) motion discontinuities, which are used to mark the boundaries between objects moving with different velocities. The accuracy of the new algorithm has been tested with artificially generated image sequences with known velocity vector fields. An iterative refinement technique yields more accurate results than the usage of higher order approximations to the first spatial and temporal derivatives. Temporal smoothing significantly improves the velocity estimates in noisy images. Displacements between consecutive images can be computed with an accuracy well below 0.1 pixel distances.