Spatiotemporal operators and optic flow

Abstract

This paper describes efforts to extract motion characteristics of a scene directly from the gray-scale data. The measurements are, by the very nature of the sampling of image data, integral values. The approach solves the ill-posedness of differentiation. A complete class of spatiotemporal operators which concisely captures the local spatiotemporal information tip to any order in space and time is proposed. Spatial and temporal scale are treated as free parameters. The operators are used to extract spatiotemporal features and to estimate the velocity field. In the estimation of the velocity field we use the generalized optic flow constraint equation, in which the signal over a region which may be subject to the flow field is conserved rather than the gray-value associated with a voxel. Examples on test images and MR-data of the Left Ventricle are shown