An FPGA-optimized architecture of horn and schunck optical flow algorithm for real-time applications

Abstract

Optical flow estimation of image sequences is one of the key elements for motion detection. However, processing the optical flow in real-time is still an open task due to its computationally expensive nature. In this paper we present an FPGA-optimized architecture for optical flow estimation based on the algorithm of Horn and Schunck. While existing FPGA-realizations are only partly real-time capable, on a Stratix IV our architecture enables the computation of the optical flow for each pixel of a frame with 640 × 512 pixels at a framerate of 30 fps in iterative and up to 4k resolution (4,096 × 2,304 pixels) at a framerate of 20 fps in full-pipelined form.