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Zhipeng Mo1

Boxin Shi2*

Sai-Kit Yeung1

Yasuyuki Matsushita2,3

1Singapore University of Technology and Design

2Artificial Intelligence Research Center, National Institute of AIST

3Osaka University

Abstract

Radiometrically calibrating the images from Internet photo collections brings photometric analysis from lab data to big image data in the wild, but conventional calibration methods cannot be directly applied to such image data. This paper presents a method to jointly perform radiometric calibration for a set of images in an Internet photo collection. By incorporating the consistency of scene reflectance for corresponding pixels in multiple images, the proposed method estimates radiometric response functions of all the images using a rank minimization framework. Our calibration aligns all response functions in an image set up to the same exponential ambiguity in a robust manner. Quantitative results using both synthetic and real data show the effectiveness of the proposed method.

Keywords: radiometric calibration, Internet photo collections

Publication:

• Radiometric Calibration for Internet Photo Collections
  Zhipeng Mo, Boxin Shi, Sai-Kit Yeung, Yasuyuki Matsushita,
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017)
  Paper, Video
  
  

  BibTex:

  @article{radiometricInt,
      author = {Zhipeng Mo and Boxin Shi and Sai-Kit Yeung and Yasuyuki Matsushita},
      title = {Radiometric Calibration for Internet Photo Collections},
      booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
      year = {2017}
  }

Acknowledgements:

We thank Joon-Young Lee for providing the code of his paper. Boxin Shi and Yasuyuki Matsushita are supported by a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO). Boxin Shi is also supported by JSPS KAKENHI Grant Number JP17K12722. Sai-Kit Yeung is supported by Singapore MOE Academic Research Fund MOE2016-T2-2- 154; Heritage Research Grant of the National Heritage Board, Singapore; SUTD Digital Manufacturing and Design (DManD) Centre which is supported by the National Research Foundation (NRF) of Singapore; the NRF, Prime Ministers Office, Singapore under its IDM Futures Funding Initiative and its Environmental & Water Technologies Strategic Research Programme and administered by the PUB, Singapores National Water Agency; this material is based on research/work supported in part by the National Research Foundation under Virtual Singapore Award No. NRF2015VSG-AA3DCM001-014.

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Results: