Low complexity optical flow using neighbor-guided semi-global matching

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

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

8 Scopus citations

Abstract

This paper presents Neighbor-Guided SemiGlobal Matching (NG-fSGM), a new method for optical flow. It is based on SGM, a popular dynamic programming algorithm for stereo vision, where the disparity of each pixel is calculated by aggregating local matching costs over the entire image to resolve local ambiguity in texture-less and occluded regions. Unlike conventional SGM, NG-fSGM operates on a subset of the search space that has been aggressively pruned based on neighboring pixels' information. Our proposed method achieves a fast approximation of SGM with significantly simpler cost aggregation and flow computation. Compared to a prior SGM extension for optical flow, the proposed NG-fSGM provides about 9x reduction in the number of computations and 5x reduction in the memory requirement with only 0.17% accuracy degradation when evaluated with Middlebury benchmark test cases.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages4483-4487
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - Aug 3 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: Sep 25 2016Sep 28 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
Country/TerritoryUnited States
CityPhoenix
Period9/25/169/28/16

Keywords

  • FSGM
  • Low complexity
  • Optical flow
  • SGM

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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