Linear Photometric Stereo using Close Lighting Images based on Intensity Differential

Zennichiro Sasaki, Fumihiko Sakaue, Jun Sato

2017

Abstract

In this paper, we propose a new linear photometric stereo method from images taken under close light sources. When an images are taken under close light source, we can obtain not only surface normal but also shape from the images. However, relationship between observed intensity and object shape is not linear, and then, we have to use non-linear optimization to estimate object shape. In order to estimate object shape by just linear estimation, we focus not only direct observed intensities, but also differentials of the intensities in this paper. By using the set of observed intensity and its differentials, we can represent relationship between object shape and intensities linearly. By this linear representation, linear estimation of object shape achieved even if obtained images are taken under close light sources. Experimental results show our proposed method can reconstruct object shape by only linear estimation efficiently and accurately.

References

  1. Brostow, G., Hernandez, C., Vogiatzis, G., Stenger, B., and Cipolla, R. (2011). Video normals from colored lights. Trans. PAMI, 33(10):2104-2114.
  2. Chen, C., Vauero, D., and Turk, M. (2011). Illumination demultiplexing from a single image. In Proc. ICCV2011, pages 17-24.
  3. Fujita, Y., Sakaue, F., and Sato, J. (2009). Linear image representation under close lighting for shape reconstruction. In Proc. International Conference on Computer Vision Theory and Applications, volume 2, pages 67- 72.
  4. Hayakawa, H. (1994). Photometric stereo under a light source with arbitrary motion. Journal of the Optical Society of America A, 11(11):3079-3089.
  5. Iwahori, Y. (1990). Reconstructing shape from shading images under point light source illumination. In Proc. of International Conference on Pattern Recognition (ICPR'90), pages 83-87.
  6. Kato, K., Sakaue, F., and Sato, J. (2010). Extended multiple view geometry for lights and cameras from photometric and geometric constraints. In Proc. 12th International Conference on Pattern Recognition (ICPR2010), pages 2110-2113.
  7. Kim, B. and Burger, P. (1991). Depth and shape from shading using the photometric stereo method. CVGIP: Image Understanding, 54(3):416-427.
  8. Okabe, T. and Sato, Y. (2006). Effects of image segmentation for approximating object appearance under near lighting. Proc. of Asian Conference on Computer Vision (ACCV2006), I:764-775.
  9. Woodham, R. (1980). Photometric method for determining surface orientation from multiple images. Optical Engineerings, 19(1):139-144.
Download


Paper Citation


in Harvard Style

Sasaki Z., Sakaue F. and Sato J. (2017). Linear Photometric Stereo using Close Lighting Images based on Intensity Differential . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 623-630. DOI: 10.5220/0006265506230630


in Bibtex Style

@conference{visapp17,
author={Zennichiro Sasaki and Fumihiko Sakaue and Jun Sato},
title={Linear Photometric Stereo using Close Lighting Images based on Intensity Differential},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={623-630},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006265506230630},
isbn={978-989-758-225-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Linear Photometric Stereo using Close Lighting Images based on Intensity Differential
SN - 978-989-758-225-7
AU - Sasaki Z.
AU - Sakaue F.
AU - Sato J.
PY - 2017
SP - 623
EP - 630
DO - 10.5220/0006265506230630