Dense Pixel-Wise Micro-motion Estimation of Object Surface by Using Low Dimensional Embedding of Laser Speckle Pattern

Ryusuke Sagawa, Yusuke Higuchi, Hiroshi Kawasaki, Ryo Furukawa, Takahiro Ito

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

Abstract

This paper proposes a method of estimating micro-motion of an object at each pixel that is too small to detect under a common setup of camera and illumination. The method introduces an active-lighting approach to make the motion visually detectable. The approach is based on speckle pattern, which is produced by the mutual interference of laser light on object’s surface and continuously changes its appearance according to the out-of-plane motion of the surface. In addition, speckle pattern becomes uncorrelated with large motion. To compensate such micro- and large motion, the method estimates the motion parameters up to scale at each pixel by nonlinear embedding of the speckle pattern into low-dimensional space. The out-of-plane motion is calculated by making the motion parameters spatially consistent across the image. In the experiments, the proposed method is compared with other measuring devices to prove the effectiveness of the method.

Original languageEnglish
Title of host publicationComputer Vision – ACCV 2020 - 15th Asian Conference on Computer Vision, 2020, Revised Selected Papers
EditorsHiroshi Ishikawa, Cheng-Lin Liu, Tomas Pajdla, Jianbo Shi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages700-715
Number of pages16
ISBN (Print)9783030695316
DOIs
Publication statusPublished - 2021
Event15th Asian Conference on Computer Vision, ACCV 2020 - Virtual, Online
Duration: Nov 30 2020Dec 4 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12623 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th Asian Conference on Computer Vision, ACCV 2020
CityVirtual, Online
Period11/30/2012/4/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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