Abstract
Interreflections exhibit a number of challenges for existing shape-from-intensity methods that only assume a direct lighting model. Removing the interreflections from scene observations is of broad interest since it enhances the accuracy of those methods. In this paper, we propose a method for removing interreflections from a single image using fluorescence. From a bispectral observation of reflective and fluorescent components recorded in distinct color channels, our method separates direct lighting from interreflections. Experimental results demonstrate the effectiveness of the proposed method on complex and dynamic scenes. In addition, we show how our method improves an existing photometric stereo method in shape recovery.
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Achar, S., Nuske, S., Narasimhan, S.G.: Compensating for motion during direct-global separation. In: Proc. of International Conference on Computer Vision (ICCV), pp. 1481–1488 (December 2013)
Forsyth, D., Zisserman, A.: Mutual illumination. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR, pp. 466–473 (June 1989)
Forsyth, D., Zisserman, A.: Shape from shading in the light of mutual illumination. Image Vision Computing 8(1), 42–49 (1990)
Y., Fu, L.A., Sato, I., Okabe, T., Sato, Y.: Separating reflective and fluorescent components using high frequency illumination in the spectral domain. In: Proc. of International Conference on Computer Vision, ICCV (2013)
Funt, B.V., Drew, M.S., Ho, J.: Color constancy from mutual reflection. International Journal of Computer Vision (IJCV) 6(1), 5–24 (1991)
Funt, B., Drew, M.: Color space analysis of mutual illumination. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI) 15(12), 1319–1326 (1993)
Glassner, A.S.: A model for fluorescence and phosphorescence. In: Photorealistic Rendering Techniques, pp. 60–70. Springer, Heidelberg (1995)
Han, S., Matsushita, Y., Sato, I., Okabe, T., Sato, Y.: Camera spectral sensitivity estimation from a single image under unknown illumination by using fluorescence. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR (2012)
Hullin, M.B., Fuchs, M., Ihrke, I., Seidel, H.P., Lensch, H.P.A.: Fluorescent immersion range scanning. ACM Trans. on Graph (ToG) 27, 87:1–87:10 (2008)
Hullin, M.B., Hanika, J., Ajdin, B., Seidel, H.P., Kautz, J., Lensch, H.P.A.: Acquisition and analysis of bispectral bidirectional reflectance and reradiation distribution functions. ACM Trans. on Graph (ToG) 29, 97:1–97:7 (2010)
Johnson, G.M., Fairchild, M.D.: Full-spectral color calculations in realistic image synthesis. IEEE Computer Graphics and Applications 19, 47–53 (1999)
Koenderink, J.J., Van Doorn, A.J.: Geometrical modes as a general method to treat diffuse interreflections in radiometry. Journal of the Optical Soceity of America (JOSA) 73(6), 843–850 (1983)
Lakowicz, J.R.: Principles of Fluorescence Spectroscopy. Springer (2006)
Lam, A., Sato, I.: Spectral modeling and relighting of reflective-fluorescent scenes. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR (2013)
Liao, M., Huang, X., Yang, R.: Interreflection removal for photometric stereo by using spectrum-dependent albedo. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 689–696 (2011)
McNamara, G., Gupta, A., Reynaert, J., Coates, T.D., Boswell, C.: Spectral imaging microscopy web sites and data. Cytometry. Part A: The Journal of the International Society for Analytical Cytology 69(8), 863–871 (2006)
Nayar, S.K., Gao, Y.: Colored interreflections and shape recovery. In: Proceedings of the Image Understanding Workshop (1992)
Nayar, S.K., Krishnan, G., Grossberg, M.D., Raskar, R.: Fast separation of direct and global components of a scene using high frequency illumination. In: ACM SIGGRAPH, pp. 935–944 (2006)
Nayar, S., Ikeuchi, K., Kanade, T.: Shape from interreflections. International Journal of Computer Vision (IJCV) 6(3), 173–195 (1991)
O’Toole, M., Mather, J., Kutulakos, K.N.: 3d shape and indirect appearance by structured light transport. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (June 2014)
Sato, I., Okabe, T., Sato, Y.: Bispectral photometric stereo based on fluorescence. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR (2012)
Sato, I., Zhang, C.: Image-based separation of reflective and fluorescent components using illumination variant and invariant color. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI) 35(12), 2866–2877 (2013)
Seitz, S.M., Matsushita, Y., Kutulakos, K.N.: A theory of inverse light transport. In: Proc. of International Conference on Computer Vision (ICCV), pp. 1440–1447 (2005)
Treibitz, T., Murez, Z., Mitchell, B.G., Kriegman, D.: Shape from fluorescence. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part VII. LNCS, vol. 7578, pp. 292–306. Springer, Heidelberg (2012)
Wilkie, A., Weidlich, A., Larboulette, C., Purgathofer, W.: A reflectance model for diffuse fluorescent surfaces. In: International Conference on Computer Graphics and Interactive Techniques, pp. 321–331 (2006)
Woodham, R.J.: Photometric method for determining surface orientation from multiple images. Optical Engineering 19(1) (1980)
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Fu, Y., Lam, A., Matsushita, Y., Sato, I., Sato, Y. (2014). Interreflection Removal Using Fluorescence. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds) Computer Vision – ECCV 2014. ECCV 2014. Lecture Notes in Computer Science, vol 8693. Springer, Cham. https://doi.org/10.1007/978-3-319-10602-1_14
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DOI: https://doi.org/10.1007/978-3-319-10602-1_14
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