A Comparison of FPGA and GPU for Real-Time Phase-based Optical Flow, Stereo, and Local Image Features
K.U.Leuven, Leuven
IEEE Transactions on Computers, 2011
@article{pauwels2011comparison,
title={A Comparison of FPGA and GPU for Real-Time Phase-based Optical Flow, Stereo, and Local Image Features},
author={Pauwels, K. and Tomasi, M. and Alonso, J.D. and Ros, E. and Van Hulle, M.M.},
journal={IEEE Transactions on Computers},
year={2011},
publisher={Published by the IEEE Computer Society}
}
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.
July 10, 2011 by hgpu
