Low Complexity, Hardware-Efficient Neighbor-Guided SGM Optical Flow for Low-Power Mobile Vision Applications

Ziyun Li, Jiang Xiang, Luyao Gong, David Blaauw, Chaitali Chakrabarti, Hun Seok Kim

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Accurate, low-latency, and energy-efficient optical flow estimation is a fundamental kernel function to enable several real-time vision applications on mobile platforms. This paper presents neighbor-guided semi-global matching (NG-fSGM), a new low-complexity optical flow algorithm tailored for low-power mobile applications. NG-fSGM obtains high accuracy optical flow by aggregating local matching costs over a semi-global region, successfully resolving local ambiguity in texture-less and occluded regions. The proposed NG-fSGM aggressively prunes the search space based on neighboring pixels' information to significantly lower the algorithm complexity from the original fSGM. As a result, NG-fSGM achieves $17.9{\times}$ reduction in the number of computations and $8.37{\times}$ reduction in memory space compared to the original fSGM without compromising its algorithm accuracy. A multicore architecture for NG-fSGM is implemented in hardware to quantify algorithm complexity and power consumption. The proposed architecture realizes NG-fSGM with overlapping blocks processed in parallel to enhance throughput and to lower power consumption. The eight-core architecture achieves 20 M pixel/s (66 frames/s for VGA) throughput with 9.6 mm2 area at 679.2-mW power consumption in 28-nm node.

Original languageEnglish (US)
Article number8408840
Pages (from-to)2191-2204
Number of pages14
JournalIEEE Transactions on Circuits and Systems for Video Technology
Issue number7
StatePublished - Jul 2019


  • Optical flow
  • VLSI
  • low power
  • multi-core accelerator
  • semi-global matching

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering


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