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Issue No.03 - May/June (2009 vol.15)
pp: 465-480
Yi Xu , Purdue University, West Lafayette
Daniel G. Aliaga , Purdue University, West Lafayette
Modeling real-world scenes, beyond diffuse objects, plays an important role in computer graphics, virtual reality, and other commercial applications. One active approach is projecting binary patterns in order to obtain correspondence and reconstruct a densely sampled 3D model. In such structured-light systems, determining whether a pixel is directly illuminated by the projector is essential to decoding the patterns. When a scene has abundant indirect light, this process is especially difficult. In this paper, we present a robust pixel classification algorithm for this purpose. Our method correctly establishes the lower and upper bounds of the possible intensity values of an illuminated pixel and of a non-illuminated pixel. Based on the two intervals, our method classifies a pixel by determining whether its intensity is within one interval but not in the other. Our method performs better than standard method due to the fact that it avoids gross errors during decoding process caused by strong inter-reflections. For the remaining uncertain pixels, we apply an iterative algorithm to reduce the inter-reflection within the scene. Thus, more points can be decoded and reconstructed after each iteration. Moreover, the iterative algorithm is carried out in an adaptive fashion for fast convergence.
Computer Graphics, Three-Dimensional Graphics and Realism, Digitization and Image Capture, Imaging geometry
Yi Xu, Daniel G. Aliaga, "An Adaptive Correspondence Algorithm for Modeling Scenes with Strong Interreflections", IEEE Transactions on Visualization & Computer Graphics, vol.15, no. 3, pp. 465-480, May/June 2009, doi:10.1109/TVCG.2008.97
[1] P. Belhumeur, D. Kriegman, and A. Yuille, “The Bas-Relief Ambiguity,” Int'l J. Computer Vision, vol. 35, no. 1, pp. 33-44, 1999.
[2] D. Caspi, N. Kiryati, and J. Shamir, “Range Imaging with Adaptive Color Structured Light,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 5, pp. 470-480, May 1998.
[3] M. Chandraker, F. Kahl, and D. Kriegman, “Reflections on theGeneralized Bas-Relief Ambiguity,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '05), pp. 788-795, 2005.
[4] T. Chen, H. Lensch, C. Fuchs, and H.P. Seidel, “Polarization and Phase-Shifting for 3D Scanning of Translucent Objects,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '07), pp. 1-8, 2007.
[5] J. Clark, E. Trucco, and L. Wolff, “Using Light Polarization in Laser Scanning,” Image and Vision Computing, vol. 15, no. 2, pp.107-117, 1997.
[6] M. Cohen and D. Greenberg, “The Hemi-Cube: A Radiosity Solution for Complex Environments,” Proc. ACM SIGGRAPH '85, pp. 31-40, 1985.
[7] B. Curless and M. Levoy, “Better Optical Triangulation through Spacetime Analysis,” Proc. Int'l Conf. Computer Vision (ICCV '95), pp. 987-994, 1995.
[8] H. Hoppe, T. DeRose, T. Duchamp, J. McDonald, and W. Stuetzle, “Surface Reconstruction from Unorganized Points,” Proc. ACM SIGGRAPH '92, pp. 71-78, 1992.
[9] S. Inokuchi, K. Sato, and F. Matsuda, “Range Imaging System for3-D Object Recognition,” Proc. Int'l Conf. Pattern Recognition (ICPR '84), pp. 806-808, 1984.
[10] L. Kobbelt and M. Botsch, “A Survey of Point-Based Techniques in Computer Graphics,” Computers and Graphics, vol. 28, no. 6, pp.801-814, 2004.
[11] T. Koninckx, P. Peers, P. Dutre, and L. Van Gool, “Scene-Adapted Structured Light,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '05), pp. 611-618, 2005.
[12] K. Kutulakos and E. Steger, “A Theory of Refractive and Specular 3D Shape by Light-Path Triangulation,” Proc. Int'l Conf. Computer Vision (ICCV '05), pp. 1448-1455, 2005.
[13] B. Lamond, P. Peers, and P. Debevec, “Fast Image-Based Separation of Diffuse and Specular Reflections,” SIGGRAPH Sketch, 2007.
[14] S. Mallick, T. Zickler, P. Belhumeur, and D. Kriegman, “Specularity Removal in Images and Videos: A PDE Approach,” Proc. European Conf. Computer Vision (ECCV '06), pp. 550-563, 2006.
[15] W. Matusik, H. Pfister, R. Ziegler, A. Ngan, and L. McMillan, “Acquisition and Rendering of Transparent and Refractive Objects,” Proc. Eurographics '02, pp. 267-278, 2002.
[16] D. Miyazaki and K. Ikeuchi, “Inverse Polarization Raytracing: Estimating Surface Shape of Transparent Objects,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '05), pp. 910-917, 2005.
[17] S. Nayar, X. Fang, and T. Boult, “Separation of Reflection Components Using Color and Polarization,” Int'l J. Computer Vision, vol. 21, no. 3, pp. 163-186, 1997.
[18] S. Nayar, “Shape Recovery Using Physical Models of Reflection and Inter-Reflection,” PhD dissertation, Carnegie Mellon Univ., 1991.
[19] S. Nayar, K. Ikeuchi, and T. Kanade, “Shape from Inter-Reflections,” Proc. Int'l Conf. Computer Vision (ICCV '90), pp. 2-11, 1990.
[20] S. Nayar, G. Krishnan, M. Grossberg, and R. Raskar, “Fast Separation of Direct and Global Components of a Scene Using High Frequency Illumination,” Proc. ACM SIGGRAPH '06, pp.935-944, 2006.
[21] J. Park and A. Kak, “3D Modeling of Optically Challenging Objects,” IEEE Trans. Visualization and Computer Graphics, vol. 14, no. 2, pp. 246-262, Mar./Apr. 2008.
[22] J. Salvi, J. Pages, and J. Batlle, “Pattern Codification Strategies inStructured Light Systems,” Pattern Recognition, vol. 37, pp.827-849, 2004.
[23] S. Seitz, Y. Matsushita, and K. Kutulakos, “A Theory of Inverse Light Transport,” Proc. Int'l Conf. Computer Vision (ICCV '05), pp.1440-1447, 2005.
[24] P. Sen, B. Chen, G. Garg, S. Marschner, M. Horowitz, M. Levoy, and H. Lensch, “Dual Photography,” Proc. ACM SIGGRAPH '05, pp. 745-755, 2005.
[25] D. Scharstein and R. Szeliski, “High-Accuracy Stereo Depth Maps Using Structured Light,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '03), pp. 195-202, 2003.
[26] D. Scharstein and R. Szeliski, “A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms,” Int'l J.Computer Vision, vol. 47, nos. 1/2/3, pp. 7-42, Apr.-June 2002.
[27] D. Skocaj and A. Leonardis, “Range Image Acquisition of Objects with Non-Uniform Albedo Using Structured Light Range Sensor,” Proc. Int'l Conf. Pattern Recognition (ICPR '00), pp. 778-781, 2000.
[28] S. Seitz, B. Curless, J. Diebel, D. Scharstein, and R. Szeliski, “A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '06), pp. 519-526, 2006.
[29] M. Tarini, H. Lensch, M. Goesele, and H.P. Seidel, “3D Acquisition of Mirroring Objects Using Striped Patterns,” Graphical Models, vol. 67, no. 4, pp. 233-259, 2005.
[30] M. Trobina, “Error Model of a Coded-light Range Sensor,” technique report, Comm. Technology Laboratory, ETH Zentrum, 1995.
[31] S. Umeyama and G. Godin, “Separation of Diffuse and Specular Components of Surface Reflection by Use of Polarization and Statistical Analysis of Images,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 5, pp. 639-647, May 2004.
[32] T. Wada, H. Ukida, and T. Matsuyama, “Shape from Shading with Interreflections Under a Proximal Light Source: Distortion-Free Copying of an Unfolded Book,” Int'l J. Computer Vision, vol. 24, no. 2, pp. 125-135, 1997.
[33] Y. Xu and D. Aliaga, “Robust Pixel Classification for 3D Modelingwith Structured Light,” Proc. Graphics Interface (GI '07), pp. 233-240, 2007.
[34] J. Yang, N. Ohnishi, D. Zhang, and N. Sugie, “Determining a Polyhedral Shape Using Interreflections,” Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR '97), pp. 110-115, 1997.
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