FPGA based high accuracy optical flow algorithm

Motion estimation of a scene is an interesting problem in computer vision since it is the basis for the dynamic analysis of a scene. However this task is computationally intensive for conventional processors. In this work, an FPGA-based hardware architecture for real-time motion estimation is proposed. The algorithm implemented in hardware is a gradient based inverse finite element method for optical flow computation. It manages the motion estimation of the image by calculating the Gradient, Laplacian, and Velocities of each pixel in a parallel design which improves computational speed. The algorithm used in this paper has been benchmarked against many of the well known algorithms and shows superior performance in terms of average angular error and standard deviation. The FPGA design is presented with preliminary results and discussed.