Using C to implement high-efficient computation of dense optical flow on FPGA-accelerated heterogeneous platforms

Abstract

High-quality algorithms for dense optical flow computation are computationally intensive. To compute them with high speed and low power is vital to make optical flow computation applicable in real-world applications. In contrast to only the Horn-Schunck model being studied on FPGA-based systems today, one of the best linear variational methods for dense optical flow computation, Combine-Brightness-Gradient, is implemented on FPGA-accelerated heterogeneous platforms in this paper. C instead of HDLs is employed and optimizing techniques based on the algorithmic parallelism and hardware architecture are introduced. Experimental results show that 30-110x improvement of the computing efficiency over CPUs was achieved. The FPGA-accelerated version is able to process 640 × 480 image at 12 fps with 0.38 J per frame, while it is 0.8 fps and around 40 J on CPUs. Through demonstrating high performance and low power of dense optical flow algorithm on FPGA-based heterogeneous platforms implemented in C, this paper shows that the off-the-shelf commodity FPGAs coupled with High-Level-Synthesis (HLS) tools could provide an available option when computational efficiency together with development speed are required.