Paper Info
Title
Low Complexity, Hardware-Efficient Neighbor-Guided SGM Optical Flow for Low-Power Mobile Vision Applications
Abstract
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 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$17.9{\times}$ </tex-math></inline-formula> reduction in the number of computations and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$8.37{\times}$ </tex-math></inline-formula> 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 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> area at 679.2-mW power consumption in 28-nm node.
Year
DOI
Venue
2019
10.1109/TCSVT.2018.2854284
IEEE Transactions on Circuits and Systems for Video Technology
Keywords
DocType
Volume
Optical flow,Complexity theory,Estimation,Power demand,Optimization,Transforms,Real-time systems
Journal
29
Issue
ISSN
Citations 
7
1051-8215
0
PageRank 
References 
Authors
0.34
8
6
Name
Order
Citations
PageRank
Ziyun Li1326.62
Xiang Jiang2109.03
Luyao Gong361.52
David Blaauw48916823.47
Chaitali Chakrabarti51978184.17
Hun-Seok Kim629427.15