Robust structured light system against subsurface scattering effects achieved by CNN-based pattern detection and decoding algorithm

Ryo Furukawa, Daisuke Miyazaki, Masashi Baba, Shinsaku Hiura, Hiroshi Kawasaki

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

Abstract

To reconstruct 3D shapes of real objects, a structured-light technique has been commonly used especially for practical purposes, such as inspection, industrial modeling, medical diagnosis, etc., because of simplicity, stability and high precision. Among them, oneshot scanning technique, which requires only single image for reconstruction, becomes important for the purpose of capturing moving objects. One open problem of oneshot scanning technique is its instability, when captured pattern is degraded by some reasons, such as strong specularity, subsurface scattering, inter-reflection and so on. One of important targets for oneshot scan is live animal, which includes human body or tissue of organ, and has subsurface scattering. In this paper, we propose a learning-based approach to solve pattern degradation caused by subsurface scattering for oneshot scan. Since patterns are significantly blurred by subsurface scattering, robust decoding technique is required, which is effectively achieved by separating the decoding process into two parts, such as pattern detection and ID recognition in our technique; both parts are implemented by CNN. To efficiently achieve robust pattern detection, we convert a line detection into segmentation problem. For robust ID recognition, we segment all the region into each ID using U-Net. In the experiments, it is shown that our technique is robust against strong subsurface scattering compared to state of the art technique.

Original languageEnglish
Title of host publicationComputer Vision – ECCV 2018 Workshops, Proceedings
EditorsLaura Leal-Taixé, Stefan Roth
PublisherSpringer Verlag
Pages372-386
Number of pages15
ISBN (Print)9783030110086
DOIs
Publication statusPublished - Jan 1 2019
Event15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany
Duration: Sep 8 2018Sep 14 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11129 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th European Conference on Computer Vision, ECCV 2018
CountryGermany
CityMunich
Period9/8/189/14/18

Fingerprint

Structured Light
Decoding
Scattering
Scanning
Line Detection
3D shape
Animals
Inspection
Moving Objects
Tissue
Degradation
Convert
Open Problems
Simplicity
Segmentation
Target
Experiments
Modeling

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Furukawa, R., Miyazaki, D., Baba, M., Hiura, S., & Kawasaki, H. (2019). Robust structured light system against subsurface scattering effects achieved by CNN-based pattern detection and decoding algorithm. In L. Leal-Taixé, & S. Roth (Eds.), Computer Vision – ECCV 2018 Workshops, Proceedings (pp. 372-386). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11129 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-11009-3_22

Robust structured light system against subsurface scattering effects achieved by CNN-based pattern detection and decoding algorithm. / Furukawa, Ryo; Miyazaki, Daisuke; Baba, Masashi; Hiura, Shinsaku; Kawasaki, Hiroshi.

Computer Vision – ECCV 2018 Workshops, Proceedings. ed. / Laura Leal-Taixé; Stefan Roth. Springer Verlag, 2019. p. 372-386 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11129 LNCS).

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

Furukawa, R, Miyazaki, D, Baba, M, Hiura, S & Kawasaki, H 2019, Robust structured light system against subsurface scattering effects achieved by CNN-based pattern detection and decoding algorithm. in L Leal-Taixé & S Roth (eds), Computer Vision – ECCV 2018 Workshops, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11129 LNCS, Springer Verlag, pp. 372-386, 15th European Conference on Computer Vision, ECCV 2018, Munich, Germany, 9/8/18. https://doi.org/10.1007/978-3-030-11009-3_22
Furukawa R, Miyazaki D, Baba M, Hiura S, Kawasaki H. Robust structured light system against subsurface scattering effects achieved by CNN-based pattern detection and decoding algorithm. In Leal-Taixé L, Roth S, editors, Computer Vision – ECCV 2018 Workshops, Proceedings. Springer Verlag. 2019. p. 372-386. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-11009-3_22
Furukawa, Ryo ; Miyazaki, Daisuke ; Baba, Masashi ; Hiura, Shinsaku ; Kawasaki, Hiroshi. / Robust structured light system against subsurface scattering effects achieved by CNN-based pattern detection and decoding algorithm. Computer Vision – ECCV 2018 Workshops, Proceedings. editor / Laura Leal-Taixé ; Stefan Roth. Springer Verlag, 2019. pp. 372-386 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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