A comparison of FPGA and GPU for real-time phase-based optical flow, stereo, and local image features

Pauwels, Karl and Tomasi, Matteo and Diaz Alonso, Javier and Ros, Eduardo and Van Hulle, Marc M.

IEEE Transactions on Computers, vol. 61(7), pp. 999–1012, 2012

Low-level computer vision algorithms have extreme computational requirements. In this work, we compare two real-time architectures developed using FPGA and GPU devices for the computation of phase-based optical flow, stereo, and local image features (energy, orientation, and phase). The presented approach requires a massive degree of parallelism to achieve real-time performance and allows us to compare FPGA and GPU design strategies and trade-offs in a much more complex scenario than previous contributions. Based on this analysis, we provide suggestions to real-time system designers for selecting the most suitable technology, and for optimizing system development on this platform, for a number of diverse applications.