Self-calibrating Polarising Radiometric Calibration

Daniel Teo Guangwei1Boxin Shi2Yinqiang Zheng3Sai-Kit Yeung1
1Information Systems Technology and Design, Singapore University of Technology and Design, Singapore
2National Engineering Laboratory for Video Technology, School of EECS, Peking University, China
3Digital Content and Media Sciences Research Division, National Institute of Informatics, Japan

Description of the problem

Description of the problem of radiometric calibration and unknown polarising angles


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


Self-calibrating polarising radiometric calibration
Daniel Teo Guangwei, Boxin Shi, Yinqiang Zheng, Sai-Kit Yeung
In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018

 author = {Daniel Teo Guangwei, Boxin Shi, Yinqiang Zheng, Sai-Kit Yeung},
 title = {Self-calibrating polarising radiometric calibration},
 booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
 year = {2018}


Daniel Teo and Sai-Kit Yeung are supported by the SUTD Digital Manufacturing and Design Centre which is supported by the Singapore National Research Foundation (NRF). Boxin Shi is supported by the Recruitment Pro- gram of Global Experts (Youth Program) in China (a.k.a. 1000 Youth Talents). Yinqiang Zheng is supported in part by JSPS KAKENHI Grant Number JP15H05918 and Mi- crosoft Research Asia through the 2017 Collaborative Re- search (Core13). Sai-Kit Yeung is also supported by Sin- gapore MOE Academic Research Fund MOE2016-T2-2- 154, Heritage Research Grant of the National Heritage Board, Singapore, and Singapore NRF under its IDM Fu- tures Funding Initiative and Virtual Singapore Award No. NRF2015VSGAA3DCM001-014.

Experimental Setup

Experimental Setup

Camera and rotating mount with polarising filter

Images of Objects

Points selected on the 2 objects captured


Results for Synthetic Data

Results from synthetic data

Results for Nikon D800E

Results for Tiger (left) and Lion (right) objects taken from Nikon D800E

Results for Canon EOS M2

Results for Tiger (left) and Lion (right) objects taken from Canon EOS M2

Undistortion Process

Showing the undistortion process