“Micron-scale light transport decomposition using interferometry”

  • ©Ioannis Gkioulekas, Anat Levin, Frédo Durand, and Todd Zickler

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Title:

    Micron-scale light transport decomposition using interferometry

Session/Category Title: Computational Illumination


Presenter(s)/Author(s):


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Abstract:


    We present a computational imaging system, inspired by the optical coherence tomography (OCT) framework, that uses interferometry to produce decompositions of light transport in small scenes or volumes. The system decomposes transport according to various attributes of the paths that photons travel through the scene, including where on the source the paths originate, their pathlengths from source to camera through the scene, their wavelength, and their polarization. Since it uses interference, the system can achieve high pathlength resolutions, with the ability to distinguish paths whose lengths differ by as little as ten microns. We describe how to construct and optimize an optical assembly for this technique, and we build a prototype to measure and visualize three-dimensional shape, direct and indirect reflection components, and properties of scattering, refractive/dispersive, and birefringent materials.

References:


    1. Abramson, N. 1983. Light-in-flight recording: high-speed holographic motion pictures of ultrafast phenomena. Applied Optics 22, 2 (Jan), 215–232.Google ScholarCross Ref
    2. Bai, J., Chandraker, M., Ng, T.-T., and Ramamoorthi, R. 2010. A Dual Theory of Inverse and Forward Light Transport. In Proceedings of the 11th European Conference on Computer Vision, ECCV’10, 294–307. Google ScholarDigital Library
    3. Cossairt, O., Matsuda, N., and Gupta, M. 2014. Digital refocusing with incoherent holography. In Computational Photography (ICCP), 2014 IEEE International Conference on, 1–9.Google Scholar
    4. Dorrington, A. A., Godbaz, J. P., Cree, M. J., Payne, A. D., and Streeter, L. V. 2011. Separating true range measurements from multi-path and scattering interference in commercial range cameras. In Proc. SPIE, vol. 7864.Google Scholar
    5. Goodman, J. W. 1968. Introduction to Fourier Optics. McGraw-Hill Book Company.Google Scholar
    6. Goodman, J. W. 2000. Statistical Optics. Wiley Classics Library.Google Scholar
    7. Gupta, M. and Agrawal, A. and Veeraraghavan, A. and Narasimhan, S. G. 2011. Structured light 3d scanning in the presence of global illumination. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, 713–720. Google ScholarDigital Library
    8. Hariharan, P. 2003. Optical interferometry. Elsevier.Google Scholar
    9. Heide, F., Hullin, M. B., Gregson, J., and Heidrich, W. 2013. Low-budget Transient Imaging Using Photonic Mixer Devices. ACM Trans. Graph. 32, 4 (July), 45:1–45:10. Google ScholarDigital Library
    10. Heide, F., Xiao, L., Kolb, A., Hullin, M. B., and Heidrich, W. 2014. Imaging in scattering media using correlation image sensors and sparse convolutional coding. Optics Express 22, 21 (Oct), 26338–26350.Google ScholarCross Ref
    11. Huang, D., Swanson, E., Lin, C., Schuman, J., Stinson, W., Chang, W., Hee, M., Flotte, T., Gregory, K., Puliafito, C., and Fujimoto, G. 1991. Optical coherence tomography. Science 254, 5035, 1178–1181.Google Scholar
    12. Jarabo, A., Marco, J., Muñoz, A., Buisan, R., Jarosz, W., and Gutierrez, D. 2014. A Framework for Transient Rendering. ACM Trans. Graph. 33, 6 (Nov.), 177:1–177:10. Google ScholarDigital Library
    13. Kadambi, A., Whyte, R., Bhandari, A., Streeter, L., Barsi, C., Dorrington, A., and Raskar, R. 2013. Coded Time of Flight Cameras: Sparse Deconvolution to Address Multipath Interference and Recover Time Profiles. ACM Trans. Graph. 32, 6 (Nov.), 167:1–167:10. Google ScholarDigital Library
    14. Levin, A., Glasner, D., Xiong, Y., Durand, F., Freeman, W., Matusik, W., and Zickler, T. 2013. Fabricating BRDFs at High Spatial Resolution Using Wave Optics. ACM Trans. Graph. 32, 4 (July), 144:1–144:14. Google ScholarDigital Library
    15. Luan, X. 2001. Experimental investigation of photonic mixer device and development of TOF 3D ranging systems based on PMD technology. PhD thesis, University of Siegen.Google Scholar
    16. Nayar, S. K., Krishnan, G., Grossberg, M. D., and Raskar, R. 2006. Fast Separation of Direct and Global Components of a Scene Using High Frequency Illumination. ACM Trans. Graph. 25, 3 (July), 935–944. Google ScholarDigital Library
    17. Ng, R., Ramamoorthi, R., and Hanrahan, P. 2003. All-frequency Shadows Using Non-linear Wavelet Lighting Approximation. ACM Trans. Graph. 22, 3 (July), 376–381. Google ScholarDigital Library
    18. O’Toole, M., and Kutulakos, K. N. 2010. Optical Computing for Fast Light Transport Analysis. ACM Trans. Graph. 29, 6 (Dec.), 164:1–164:12. Google ScholarDigital Library
    19. O’Toole, M., Raskar, R., and Kutulakos, K. N. 2012. Primal-dual Coding to Probe Light Transport. ACM Trans. Graph. 31, 4 (July), 39:1–39:11. Google ScholarDigital Library
    20. O’Toole, M., Mather, J., and Kutulakos, K. 2014. 3D Shape and Indirect Appearance by Structured Light Transport. In Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, 3246–3253. Google ScholarDigital Library
    21. O’Toole, M., Heide, F., Xiao, L., Hullin, M. B., Heidrich, W., and Kutulakos, K. N. 2014. Temporal Frequency Probing for 5D Transient Analysis of Global Light Transport. ACM Trans. Graph. 33, 4 (July), 87:1–87:11. Google ScholarDigital Library
    22. Peers, P., Mahajan, D. K., Lamond, B., Ghosh, A., Matusik, W., Ramamoorthi, R., and Debevec, P. 2009. Compressive Light Transport Sensing. ACM Trans. Graph. 28, 1 (Feb.), 3:1–3:18. Google ScholarDigital Library
    23. Reddy, D., Ramamoorthi, R., and Curless, B. 2012. Frequency-space Decomposition and Acquisition of Light Transport Under Spatially Varying Illumination. In Proceedings of the 12th European Conference on Computer Vision, ECCV’12, 596–610. Google ScholarDigital Library
    24. Schwarte, R., Heinol, H.-G., Xu, Z., and Hartmann, K. 1995. New active 3D vision system based on rf-modulation interferometry of incoherent light. In Proc. SPIE, vol. 2588.Google Scholar
    25. Sen, P., Chen, B., Garg, G., Marschner, S. R., Horowitz, M., Levoy, M., and Lensch, H. P. A. 2005. Dual Photography. ACM Trans. Graph. 24, 3 (July), 745–755. Google ScholarDigital Library
    26. Velten, A., Wu, D., Jarabo, A., Masia, B., Barsi, C., Joshi, C., Lawson, E., Bawendi, M., Gutierrez, D., and Raskar, R. 2013. Femto-photography: Capturing and Visualizing the Propagation of Light. ACM Trans. Graph. 32, 4 (July), 44:1–44:8. Google ScholarDigital Library
    27. Wang, J., Dong, Y., Tong, X., Lin, Z., and Guo, B. 2009. Kernel Nyström Method for Light Transport. ACM Trans. Graph. 28, 3 (July), 29:1–29:10. Google ScholarDigital Library
    28. Wu, D., Velten, A., OToole, M., Masia, B., Agrawal, A., Dai, Q., and Raskar, R. 2014. Decomposing Global Light Transport Using Time of Flight Imaging. International Journal of Computer Vision 107, 2, 123–138. Google ScholarDigital Library
    29. Wu, D., Wetzstein, G., Barsi, C., Willwacher, T., Dai, Q., and Raskar, R. 2014. Ultra-fast Lensless Computational Imaging through 5D Frequency Analysis of Time-resolved Light Transport. International Journal of Computer Vision 110, 2, 128–140. Google ScholarDigital Library


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