Configurable and scalable belief propagation accelerator for computer vision

Jungwook Choi, Rob A. Rutenbar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We demonstrate a novel FPGA-based accelerator architecture that can tackle a range of standard computer vision (CV) problems, with scalable performance and attractive speedups. The architecture relies on multiple pipelined processing elements (PEs) that can be configured to support various belief propagation (BP) settings for different CV tasks. Inside each PE, innovative implementation of Jump Flooding for efficient computation of BP solves the core configurability challenge. A novel block-parallel memory interface supports parallelization by distributing BP inference workloads across the PEs. Experimental results demonstrate that our accelerator achieves scalable performance with 11-41× speedup over standard sequential CPU implementations across a subset of well-known Middlebury and OpenGM benchmarks, with no compromise in quality of inference results. To the best of our knowledge, this is the first FPGA hardware implementation of BP capable of running a range of standard CV benchmarks with significant speedups.

Original languageEnglish (US)
Title of host publicationFPL 2016 - 26th International Conference on Field-Programmable Logic and Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9782839918442
DOIs
StatePublished - Sep 26 2016
Event26th International Conference on Field-Programmable Logic and Applications, FPL 2016 - Lausanne, Switzerland
Duration: Aug 29 2016Sep 2 2016

Publication series

NameFPL 2016 - 26th International Conference on Field-Programmable Logic and Applications

Other

Other26th International Conference on Field-Programmable Logic and Applications, FPL 2016
CountrySwitzerland
CityLausanne
Period8/29/169/2/16

Keywords

  • Belief propagation
  • Markov random field
  • computer vision
  • field programmable gate arrays

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Control and Optimization

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