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A Comparison of FPGA and GPU for Real-Time Phase-based Optical Flow, Stereo, and Local Image Features

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

}

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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.
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