A modified space frequency decomposition algorithm for visual motion

In this paper, we present a method to decompose visual motion represented by computed optical flow using an over-complete dictionary of space frequency atoms. This is accomplished by a modified matching pursuit procedure which successively selects space and frequency localized atoms from this dictionary. In effect, this decomposition reveals the structure of optical flow field such that areas with motion at different spatial location and scale are identified. In addition, our method maintains the original resolution of the image when performing the decomposition at each scale. This minimizes the amount of the information lost in the decomposition process. We perform experiments using both synthetic and real image data sets to demonstrate the effectiveness of the proposed method.