research-article

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

Authors:

Marc M. Van HulleAuthors Info & Claims

IEEE Transactions on Computers, Volume 61, Issue 7

Pages 999 - 1012

https://doi.org/10.1109/TC.2011.120

Published: 01 July 2012 Publication History

Abstract

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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Pfleger SPlentz PRocha RPereira ACastro M(2022)Real-time video denoising on multicores and GPUs with Kalman-based and Bilateral filters fusionJournal of Real-Time Image Processing10.1007/s11554-016-0659-y16:5(1629-1642)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.1007/s11554-016-0659-y
Hadj Fredj AMalek J(2021)FPGA-accelerated anisotropic diffusion filter based on SW/HW-codesign for medical imagesJournal of Real-Time Image Processing10.1007/s11554-021-01100-318:6(2429-2440)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1007/s11554-021-01100-3
Nguyen DEl Ouardi ARodriguez SBouaziz S(2021)FPGA implementation of HOOFR bucketing extractor-based real-time embedded SLAM applicationsJournal of Real-Time Image Processing10.1007/s11554-020-00986-918:3(525-538)Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1007/s11554-020-00986-9
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A Comparison of FPGA and GPU for Real-Time Phase-Based Optical Flow, Stereo, and Local Image Features
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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cover image IEEE Transactions on Computers

IEEE Transactions on Computers Volume 61, Issue 7

July 2012

144 pages

ISSN:0018-9340

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Publisher

IEEE Computer Society

United States

Publication History

Published: 01 July 2012

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Pfleger SPlentz PRocha RPereira ACastro M(2022)Real-time video denoising on multicores and GPUs with Kalman-based and Bilateral filters fusionJournal of Real-Time Image Processing10.1007/s11554-016-0659-y16:5(1629-1642)Online publication date: 11-Mar-2022
https://dl.acm.org/doi/10.1007/s11554-016-0659-y
Hadj Fredj AMalek J(2021)FPGA-accelerated anisotropic diffusion filter based on SW/HW-codesign for medical imagesJournal of Real-Time Image Processing10.1007/s11554-021-01100-318:6(2429-2440)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1007/s11554-021-01100-3
Nguyen DEl Ouardi ARodriguez SBouaziz S(2021)FPGA implementation of HOOFR bucketing extractor-based real-time embedded SLAM applicationsJournal of Real-Time Image Processing10.1007/s11554-020-00986-918:3(525-538)Online publication date: 1-Jun-2021
https://dl.acm.org/doi/10.1007/s11554-020-00986-9
Chang CZhong ZLiou JBazargan KNeuendorffer S(2019)A FPGA Implementation of Farneback Optical Flow by High-Level SynthesisProceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays10.1145/3289602.3294005(309-309)Online publication date: 20-Feb-2019
https://dl.acm.org/doi/10.1145/3289602.3294005
Kazmi MAziz AAkhtar P(2019)An efficient and compact row buffer architecture on FPGA for real-time neighbourhood image processingJournal of Real-Time Image Processing10.1007/s11554-017-0690-716:5(1845-1858)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s11554-017-0690-7
Kazmi MAziz AKundi D(2019)A Pareto-Optimal Multi-filter Architecture on FPGA for Image Processing ApplicationsCircuits, Systems, and Signal Processing10.1007/s00034-019-01083-438:10(4762-4786)Online publication date: 1-Oct-2019
https://dl.acm.org/doi/10.1007/s00034-019-01083-4
Kechiche LTouil LOuni B(2018)Toward the Implementation of an ASIC-Like System on FPGA for Real-Time Video Processing with Power ReductionInternational Journal of Reconfigurable Computing10.1155/2018/28435822018Online publication date: 22-Apr-2018
https://dl.acm.org/doi/10.1155/2018/2843582
Chen ABiglari-Abhari MWang KBouzerdoum ATivive F(2018)Convolutional neural network acceleration with hardware/software co-designApplied Intelligence10.1007/s10489-017-1007-z48:5(1288-1301)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1007/s10489-017-1007-z
O’brien KPietri IReddy RLastovetsky ASakellariou R(2017)A Survey of Power and Energy Predictive Models in HPC Systems and ApplicationsACM Computing Surveys10.1145/307881150:3(1-38)Online publication date: 29-Jun-2017
https://dl.acm.org/doi/10.1145/3078811
Leong PAmano HAnderson JBertels KCardoso JDiessel OGogniat GHutton MLee JLuk WLysaght PPlatzner MPrasanna VRissa TSilvano CSo HWang Y(2017)The First 25 Years of the FPL ConferenceACM Transactions on Reconfigurable Technology and Systems10.1145/299646810:2(1-17)Online publication date: 22-Mar-2017
https://dl.acm.org/doi/10.1145/2996468
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Performance Comparison of Graphics Processors to Reconfigurable Logic: A Case Study

FPGA based real-time on-road stereo vision system

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