Derivation of optical flow using a spatiotemporal-Frequency approach

We advance in this paper the spatiotemporal-frequency (STF) approach for computing the optical flow of a time-varying image. STF flow derivation provides an attractive alternative to earlier approaches based on (1) feature correspondence, (2) spatiotemporal gradients, and (3) Fourier-phase changes. After briefly surveying these three earlier approaches to flow computation, we provide an historical overview of the development of the STF approach. Then an improved STF method for flow derivation that has recently been developed by the authors is presented along with experimental results that demonstrate its use. The STF yields a dense time and spatially varying 2D optical flow field for each image frame. We conclude by showing that STF derivation (a) promises substantially improved performance over the flow computation methods, and (b) provides a partial explanation of motion coherence as observed in human vision.