Material Classification Using Raw Time-of-Flight Measurements

Shuochen Su; Felix Heide; Robin Swanson; Jonathan Klein; Clara Callenberg; Matthias Hullin; Wolfgang Heidrich

doi:10.1109/CVPR.2016.381

Material Classification Using Raw Time-of-Flight Measurements

Shuochen Su, Felix Heide, Robin Swanson, Jonathan Klein, Clara Callenberg, Matthias Hullin, Wolfgang Heidrich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

43 Scopus citations

Abstract

We propose a material classification method using raw time-of-flight (ToF) measurements. ToF cameras capture the correlation between a reference signal and the temporal response of material to incident illumination. Such measurements encode unique signatures of the material, i.e. the degree of subsurface scattering inside a volume. Subsequently, it offers an orthogonal domain of feature representation compared to conventional spatial and angular reflectance-based approaches. We demonstrate the effectiveness, robustness, and efficiency of our method through experiments and comparisons of real-world materials.

Original language	English (US)
Title of host publication	Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
Publisher	IEEE Computer Society
Pages	3503-3511
Number of pages	9
ISBN (Electronic)	9781467388504
DOIs	https://doi.org/10.1109/CVPR.2016.381
State	Published - Dec 9 2016
Externally published	Yes
Event	29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 - Las Vegas, United States Duration: Jun 26 2016 → Jul 1 2016

Publication series

Name	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume	2016-December
ISSN (Print)	1063-6919

Conference

Conference	29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016
Country/Territory	United States
City	Las Vegas
Period	6/26/16 → 7/1/16

All Science Journal Classification (ASJC) codes

Software
Computer Vision and Pattern Recognition

Access to Document

10.1109/CVPR.2016.381

Cite this

Su, S., Heide, F., Swanson, R., Klein, J., Callenberg, C., Hullin, M., & Heidrich, W. (2016). Material Classification Using Raw Time-of-Flight Measurements. In Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 (pp. 3503-3511). Article 7780750 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 2016-December). IEEE Computer Society. https://doi.org/10.1109/CVPR.2016.381

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title = "Material Classification Using Raw Time-of-Flight Measurements",

abstract = "We propose a material classification method using raw time-of-flight (ToF) measurements. ToF cameras capture the correlation between a reference signal and the temporal response of material to incident illumination. Such measurements encode unique signatures of the material, i.e. the degree of subsurface scattering inside a volume. Subsequently, it offers an orthogonal domain of feature representation compared to conventional spatial and angular reflectance-based approaches. We demonstrate the effectiveness, robustness, and efficiency of our method through experiments and comparisons of real-world materials.",

author = "Shuochen Su and Felix Heide and Robin Swanson and Jonathan Klein and Clara Callenberg and Matthias Hullin and Wolfgang Heidrich",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 ; Conference date: 26-06-2016 Through 01-07-2016",

year = "2016",

month = dec,

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doi = "10.1109/CVPR.2016.381",

language = "English (US)",

series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

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Su, S, Heide, F, Swanson, R, Klein, J, Callenberg, C, Hullin, M & Heidrich, W 2016, Material Classification Using Raw Time-of-Flight Measurements. in Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016., 7780750, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2016-December, IEEE Computer Society, pp. 3503-3511, 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, United States, 6/26/16. https://doi.org/10.1109/CVPR.2016.381

Material Classification Using Raw Time-of-Flight Measurements. / Su, Shuochen; Heide, Felix; Swanson, Robin et al.
Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016. IEEE Computer Society, 2016. p. 3503-3511 7780750 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; Vol. 2016-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Material Classification Using Raw Time-of-Flight Measurements

AU - Su, Shuochen

AU - Heide, Felix

AU - Swanson, Robin

AU - Klein, Jonathan

AU - Callenberg, Clara

AU - Hullin, Matthias

AU - Heidrich, Wolfgang

PY - 2016/12/9

Y1 - 2016/12/9

N2 - We propose a material classification method using raw time-of-flight (ToF) measurements. ToF cameras capture the correlation between a reference signal and the temporal response of material to incident illumination. Such measurements encode unique signatures of the material, i.e. the degree of subsurface scattering inside a volume. Subsequently, it offers an orthogonal domain of feature representation compared to conventional spatial and angular reflectance-based approaches. We demonstrate the effectiveness, robustness, and efficiency of our method through experiments and comparisons of real-world materials.

AB - We propose a material classification method using raw time-of-flight (ToF) measurements. ToF cameras capture the correlation between a reference signal and the temporal response of material to incident illumination. Such measurements encode unique signatures of the material, i.e. the degree of subsurface scattering inside a volume. Subsequently, it offers an orthogonal domain of feature representation compared to conventional spatial and angular reflectance-based approaches. We demonstrate the effectiveness, robustness, and efficiency of our method through experiments and comparisons of real-world materials.

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DO - 10.1109/CVPR.2016.381

M3 - Conference contribution

AN - SCOPUS:84986325552

T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

SP - 3503

EP - 3511

BT - Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016

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T2 - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016

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Su S, Heide F, Swanson R, Klein J, Callenberg C, Hullin M et al. Material Classification Using Raw Time-of-Flight Measurements. In Proceedings - 29th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016. IEEE Computer Society. 2016. p. 3503-3511. 7780750. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). doi: 10.1109/CVPR.2016.381

Material Classification Using Raw Time-of-Flight Measurements

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