Spatiotemporal model-based optic flow estimation

Nuno Vasconcelos, Andrew Lippman

Abstract: We introduce a spatiotemporal model-based algorithm capable of providing estimates of optic flow which are coherent along a set of video frames. The algorithm is based on a spatiotemporal motion model that consists of a quadratic constraint in time and an affine constraint in space. Optic flow is computed through a delayed-decision process that incorporates knowledge about both image correlation along time, and the goodness of fit to the underlying motion-model. The temporal coherence and parametric nature of the recovered optic flow can facilitate interactive access to the video stream and improve the efficiency of tasks such as video compression, interpolation or classification.