A general model for visual motion detection

We propose a general model for detection of both first-order motion and second-order motion. In this model an input stimulus is divided into a number of partially overlapping spatiotemporal local regions. Spatiotemporal frequency analysis is done for every local region using Gabor filters, then the input stimulus (original spatiotemporal signal) is replaced by the outputs of Gabor filters. Local motion is detected by applying Gabor motion detectors to each local spatiotemporal pattern depicted by each local feature value. Outputs of all the detectors are integrated to give the final output for global motion of the input stimulus. The model was simulated on a computer and was confirmed to correctly detect second-order motion as well as first-order motion.