Self-Calibrating Polarising Radiometric Calibration

Daniel Teo Guangwei; Boxin Shi; Yinqiang Zheng; Sai Kit Yeung

doi:10.1109/CVPR.2018.00299

Self-Calibrating Polarising Radiometric Calibration

Daniel Teo Guangwei, Boxin Shi^*, Yinqiang Zheng, Sai Kit Yeung

^*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

6 Citations (Scopus)

Abstract

We present a self-calibrating polarising radiometric calibration method. From a set of images taken from a single viewpoint under different unknown polarising angles, we recover the inverse camera response function and the polarising angles relative to the first angle. The problem is solved in an integrated manner, recovering both of the unknowns simultaneously. The method exploits the fact that the intensity of polarised light should vary sinusoidally as the polarising filter is rotated, provided that the response is linear. It offers the first solution to demonstrate the possibility of radiometric calibration through polarisation. We evaluate the accuracy of our proposed method using synthetic data and real world objects captured using different cameras. The self-calibrated results were found to be comparable with those from multiple exposure sequence.

Original language	English
Title of host publication	Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018
Publisher	IEEE Computer Society
Pages	2831-2839
Number of pages	9
ISBN (Electronic)	9781538664209
DOIs	https://doi.org/10.1109/CVPR.2018.00299
Publication status	Published - 14 Dec 2018
Externally published	Yes
Event	31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 - Salt Lake City, United States Duration: 18 Jun 2018 → 22 Jun 2018

Publication series

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

Conference

Conference	31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018
Country/Territory	United States
City	Salt Lake City
Period	18/06/18 → 22/06/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Access to Document

10.1109/CVPR.2018.00299

Cite this

Guangwei, D. T., Shi, B., Zheng, Y., & Yeung, S. K. (2018). Self-Calibrating Polarising Radiometric Calibration. In Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 (pp. 2831-2839). Article 8578397 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition). IEEE Computer Society. https://doi.org/10.1109/CVPR.2018.00299

@inproceedings{128a239567ca43e9946aef0b3cb42ca5,

title = "Self-Calibrating Polarising Radiometric Calibration",

abstract = "We present a self-calibrating polarising radiometric calibration method. From a set of images taken from a single viewpoint under different unknown polarising angles, we recover the inverse camera response function and the polarising angles relative to the first angle. The problem is solved in an integrated manner, recovering both of the unknowns simultaneously. The method exploits the fact that the intensity of polarised light should vary sinusoidally as the polarising filter is rotated, provided that the response is linear. It offers the first solution to demonstrate the possibility of radiometric calibration through polarisation. We evaluate the accuracy of our proposed method using synthetic data and real world objects captured using different cameras. The self-calibrated results were found to be comparable with those from multiple exposure sequence.",

author = "Guangwei, \{Daniel Teo\} and Boxin Shi and Yinqiang Zheng and Yeung, \{Sai Kit\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018 ; Conference date: 18-06-2018 Through 22-06-2018",

year = "2018",

month = dec,

day = "14",

doi = "10.1109/CVPR.2018.00299",

language = "English",

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

publisher = "IEEE Computer Society",

pages = "2831--2839",

booktitle = "Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018",

}

Guangwei, DT, Shi, B, Zheng, Y & Yeung, SK 2018, Self-Calibrating Polarising Radiometric Calibration. in Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018., 8578397, Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, pp. 2831-2839, 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018, Salt Lake City, United States, 18/06/18. https://doi.org/10.1109/CVPR.2018.00299

Self-Calibrating Polarising Radiometric Calibration. / Guangwei, Daniel Teo; Shi, Boxin; Zheng, Yinqiang et al.
Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018. IEEE Computer Society, 2018. p. 2831-2839 8578397 (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Self-Calibrating Polarising Radiometric Calibration

AU - Guangwei, Daniel Teo

AU - Shi, Boxin

AU - Zheng, Yinqiang

AU - Yeung, Sai Kit

PY - 2018/12/14

Y1 - 2018/12/14

N2 - We present a self-calibrating polarising radiometric calibration method. From a set of images taken from a single viewpoint under different unknown polarising angles, we recover the inverse camera response function and the polarising angles relative to the first angle. The problem is solved in an integrated manner, recovering both of the unknowns simultaneously. The method exploits the fact that the intensity of polarised light should vary sinusoidally as the polarising filter is rotated, provided that the response is linear. It offers the first solution to demonstrate the possibility of radiometric calibration through polarisation. We evaluate the accuracy of our proposed method using synthetic data and real world objects captured using different cameras. The self-calibrated results were found to be comparable with those from multiple exposure sequence.

AB - We present a self-calibrating polarising radiometric calibration method. From a set of images taken from a single viewpoint under different unknown polarising angles, we recover the inverse camera response function and the polarising angles relative to the first angle. The problem is solved in an integrated manner, recovering both of the unknowns simultaneously. The method exploits the fact that the intensity of polarised light should vary sinusoidally as the polarising filter is rotated, provided that the response is linear. It offers the first solution to demonstrate the possibility of radiometric calibration through polarisation. We evaluate the accuracy of our proposed method using synthetic data and real world objects captured using different cameras. The self-calibrated results were found to be comparable with those from multiple exposure sequence.

UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000457843602099

UR - https://openalex.org/W2799078665

UR - https://www.scopus.com/pages/publications/85062847410

U2 - 10.1109/CVPR.2018.00299

DO - 10.1109/CVPR.2018.00299

M3 - Conference Paper published in a book

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

SP - 2831

EP - 2839

BT - Proceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018

PB - IEEE Computer Society

T2 - 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2018

Y2 - 18 June 2018 through 22 June 2018

ER -

Self-Calibrating Polarising Radiometric Calibration

Abstract

Publication series

Conference

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this