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Direct and Global Component Separation from a Single Image Using Basis Representation

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Computer Vision – ACCV 2016 (ACCV 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10113))

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Abstract

Previous research showed that the separation of direct and global components could be done with a single image by assuming neighboring scene points have similar direct and global components, but it normally leads to loss of spatial resolution of the results. To tackle such problem, we present a novel approach for separating direct and global components of a scene in full spatial resolution from a single captured image, which employs linear basis representation to approximate direct and global components. Due to the basis dependency of these two components, high frequency light pattern is utilized to modulate the frequency of direct components, which can effectively improve stability of linear model between direct and global components. The effectiveness of our approach is demonstrated on both simulated and real images captured by a standard off-the-shelf camera and a projector mounted in a coaxial system. Our results show better visual quality and less error compared with those obtained by the conventional single-shot approach on both still and moving objects.

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Notes

  1. 1.

    All these images contain both direct and global components, thus it is reasonable to learn the PCA basis on this general image dataset.

References

  1. Nayar, S., Krishnan, G., Grossberg, M.D., Raskar, R.: Fast separation of direct and global components of a scene using high frequency illumination. ACM Trans. Graph. Proc. ACM SIGGRAPH 25(3), 935–944 (2006)

    Google Scholar 

  2. Morris, N., Kutulakos, K.: Reconstructing the surface of inhomogeneous transparent scenes by scatter-trace photography. In: IEEE 11th International Conference on Computer Vision (ICCV), pp. 1–8 (2007)

    Google Scholar 

  3. Chen, T., Seidel, H.P., Lensch, H.: Modulated phase-shifting for 3D scanning. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–8 (2008)

    Google Scholar 

  4. Talvala, E.V., Adams, A., Horowitz, M., Levoy, M.: Veiling glare in high dynamic range imaging. In: ACM SIGGRAPH 2007 Papers, SIGGRAPH 2007, New York, NY, USA (2007)

    Google Scholar 

  5. Gupta, M., Narasimhan, S., Schechner, Y.: On controlling light transport in poor visibility environments. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1–8 (2008)

    Google Scholar 

  6. Achar, S., Nuske, S., Narasimhan, S.: Compensating for motion during direct-global separation. In: IEEE International Conference on Computer Vision (ICCV), pp. 1481–1488 (2013)

    Google Scholar 

  7. Gu, J., Kobayashi, T., Gupta, M., Nayar, S.K.: Multiplexed illumination for scene recovery in the presence of global illumination. In: IEEE International Conference on Computer Vision (ICCV), pp. 1–8 (2011)

    Google Scholar 

  8. Gupta, M., Tian, Y., Narasimhan, S., Zhang, L.: A combined theory of defocused illumination and global light transport. Int. J. Comput. Vis. 98, 146–167 (2012)

    Article  MathSciNet  Google Scholar 

  9. Achar, S., Narasimhan, S.G.: Multi focus structured light for recovering scene shape and global illumination. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8689, pp. 205–219. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10590-1_14

    Google Scholar 

  10. Gupta, M., Agrawal, A., Veeraraghavan, A., Narasimhan, S.G.: A practical approach to 3D scanning in the presence of interreflections, subsurface scattering and defocus. Int. J. Comput. Vis. 102, 33–55 (2013)

    Article  Google Scholar 

  11. Reddy, D., Ramamoorthi, R., Curless, B.: Frequency-space decomposition and acquisition of light transport under spatially varying illumination. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7577, pp. 596–610. Springer, Heidelberg (2012). doi:10.1007/978-3-642-33783-3_43

    Chapter  Google Scholar 

  12. Bai, J., Chandraker, M., Ng, T.T., Ramamoorthi, R.: A dual theory of inverse and forward light transport. In: European Conference on Computer Vision, pp. 1–8 (2010)

    Google Scholar 

  13. Tariq, S., Gardner, A., Llamas, I., Jones, A., Debevec, P., Turk, G.: Efficient estimation of spatially varying subsurface scattering parameters for relighting. ICT Technical Report ICT TR 01 2006, University of Southern California Institute for Creative Technologies (2006)

    Google Scholar 

  14. Ghosh, A., Hawkins, T., Peers, P., Frederiksen, S., Debevec, P.: Practical modeling and acquisition of layered facial reflectance. ACM Trans. Graph. 27, 139:1–139:10 (2008)

    Google Scholar 

  15. Mukaigawa, Y., Suzuki, K., Yagi, Y.: Analysis of subsurface scattering based on dipole approximation. Inf. Media Technol. 4, 951–961 (2009)

    Google Scholar 

  16. Munoz, A., Echevarria, J.I., Seron, F.J., Lopez-Moreno, J., Glencross, M., Gutierrez, D.: BSSRDF estimation from single images. Comput. Graph. Forum 30, 455–464 (2011)

    Article  Google Scholar 

  17. Liu, Y., Qin, X., Xu, S., Nakamae, E., Peng, Q.: Light source estimation of outdoor scenes for mixed reality. Vis. Comput. 25, 637–646 (2009)

    Article  Google Scholar 

  18. Narasimhan, S.G., Koppal, S.J., Yamazaki, S.: Temporal dithering of illumination for fast active vision. In: Proceedings of European Conference on Computer Vision, pp. 830–844 (2008)

    Google Scholar 

  19. Wu, D., O’Toole, M., Velten, A., Agrawal, A., Raskar, R.: Decomposing global light transport using time of flight imaging. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 366–373 (2012)

    Google Scholar 

  20. Owu’Toole, M., Raskar, R., Kutulakos, K.N.: Primal-dual coding to probe light transport. ACM Trans. Graph. 31, 39:1–39:11 (2012)

    Google Scholar 

  21. O’Toole, M., Achar, S., Narasimhan, S.G., Kutulakos, K.N.: Homogeneous codes for energy-efficient illumination and imaging. ACM Trans. Graph. 34, 35:1–35:13 (2015)

    Google Scholar 

  22. Yang, C.Y., Yang, M.H.: Fast direct super-resolution by simple functions. In: Proceedings of IEEE International Conference on Computer Vision (2013)

    Google Scholar 

  23. Amano, T.: Projection center calibration for a co-located projector camera system. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 449–454 (2014)

    Google Scholar 

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Acknowledgements

This work was supported in part by Grant-in-Aid for Scientific Research on Innovative Areas (No.15H05918) from MEXT, Japan.

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Authors and Affiliations

  1. Tokyo Institute of Technology, Tokyo, Japan

    Art Subpa-asa & Imari Sato

  2. The University of Tokyo, Tokyo, Japan

    Ying Fu

  3. National Institute of Informatics, Tokyo, Japan

    Yinqiang Zheng & Imari Sato

  4. Wakayama University, Wakayama, Japan

    Toshiyuki Amano

Authors
  1. Art Subpa-asa
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  2. Ying Fu
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  3. Yinqiang Zheng
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  4. Toshiyuki Amano
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  5. Imari Sato
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Corresponding author

Correspondence to Art Subpa-asa .

Editor information

Editors and Affiliations

  1. National Tsing Hua University, Hsinchu, Taiwan

    Shang-Hong Lai

  2. Graz University of Technology, Graz, Austria

    Vincent Lepetit

  3. Drexel University, Philadelphia, Pennsylvania, USA

    Ko Nishino

  4. The University of Tokyo , Tokyo, Japan

    Yoichi Sato

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Subpa-asa, A., Fu, Y., Zheng, Y., Amano, T., Sato, I. (2017). Direct and Global Component Separation from a Single Image Using Basis Representation. In: Lai, SH., Lepetit, V., Nishino, K., Sato, Y. (eds) Computer Vision – ACCV 2016. ACCV 2016. Lecture Notes in Computer Science(), vol 10113. Springer, Cham. https://doi.org/10.1007/978-3-319-54187-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-54187-7_7

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-54187-7

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