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A Self-Calibrating Method for Photogeometric Acquisition of 3D Objects
April 2010 (vol. 32 no. 4)
pp. 747-754
Daniel G. Aliaga, Purdue University, West Lafayette
Yi Xu, Purdue University, West Lafayette
We present a self-calibrating photogeometric method using only off--the-shelf hardware that enables quickly and robustly obtaining multimillion point-sampled and colored models of real-world objects. Some previous efforts use a priori calibrated systems to separately acquire geometric and photometric information. Our key enabling observation is that a digital projector can be simultaneously used as either an active light source or as a virtual camera (as opposed to a digital camera, which cannot be used for both). We present our self--calibrating and multiviewpoint 3D acquisition method, based on structured light, which simultaneously obtains mutually registered surface position and surface normal information and produces a single high-quality model. Acquisition processing freely alternates between using a geometric setup and using a photometric setup with the same hardware configuration. Further, our approach generates reconstructions at the resolution of the camera and not only the projector. We show the results of capturing several high-quality models of real--world objects.

[1] D. Aliaga and Y. Xu, "Photogeometric Structured Light: A Self-Calibrating and Multi-Viewpoint Framework for Accurate 3D Modeling," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
[2] R. Basri, D. Jacobs, and I. Kemelmacher, "Photometric Stereo with General Unknown Lighting," Int'l J. Computer Vision, vol. 72, no. 3, pp. 239-257, 2007.
[3] J. Batlle, E. Mouaddib, and J. Salvi, "Recent Progress in Coded Structured Light as a Technique to Solve the Correspondence Problem: A Survey," Pattern Recognition, vol. 31, no. 7, pp. 963-982, 1998.
[4] P. Belhumeur, D. Kriegman, and A. Yuille, "The Bas-Relief Ambiguity," Int'l J. Computer Vision, vol. 35, no. 1, pp. 33-44, 1999.
[5] J. Davis, D. Nehab, R. Ramamoorthi, and S. Rusinkiewicz, "Spacetime Stereo: A Unifying Frame-Work for Depth from Triangulation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 2, pp. 296-302, Feb. 2005.
[6] R. Frankot and R. Chellappa, "A Method for Enforcing Integrability in Shape from Shading Algorithms," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 10, no. 4, pp. 439-451, Apr. 1988.
[7] R. Furukawa and H. Kawasaki, "Uncalibrated Multiple Image Stereo System with Arbitrarily Movable Camera and Projector for Wide Range Scanning," Proc. Int'l Conf. 3-D Digital Imaging and Modeling, pp. 302-309, 2005.
[8] D. Goldman, B. Curless, A. Hertzmann, and S. Seitz, "Shape and Spatially-Varying BRDFs from Photometric Stereo," Proc. IEEE Int'l Conf. Computer Vision, pp. 341-348, 2005.
[9] E. Hemayed, "A Survey of Camera Self-Calibration," Proc. IEEE Conf. Advanced Video Signal Based Surveillance, pp. 351-357, 2003.
[10] C. Hernandez, G. Vogiatzis, and R. Cipolla, "Multi-View Photometric Stereo," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 3, pp. 548-554, Mar. 2008.
[11] S. Inokuchi, K. Sato, and F. Matsuda, "Range Imaging System for 3-D Object Recognition," Proc. Int'l Conf. Pattern Recognition, pp. 806-808, 1984.
[12] T. Koninckx, A. Griesser, and L. van Gool, "Real-Time Range Scanning of Deformable Surfaces by Adaptively Coded Structured Light," Proc. Int'l Conf. 3-D Digital Imaging and Modeling, pp. 293-300, 2003.
[13] J. Lim, J. Ho, M. Yang, and D. Kriegman, "Passive Photometric Stereo from Motion," Proc. IEEE Int'l Conf. Computer Vision, pp. 1635-1642, 2005.
[14] J. Lu and J. Little, "Reflectance and Shape from Images Using a Collinear Light Source," Int'l J. Computer Vision, vol. 32, no. 3, pp. 213-240, 1999.
[15] S. Mallick, T. Zickler, D. Kriegman, and P. Belhumeur, "Beyond Lambert: Reconstructing Specular Surfaces Using Color," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 619-626, 2005.
[16] D. Nehab, S. Rusinkiewicz, J. Davis, and R. Ramamoorthi, "Efficiently Combining Positions and Normals for Precise 3D Geometry," ACM Trans. Graphics, vol. 24, no. 3, pp. 536-543, 2005.
[17] 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.
[18] M. Pollefeys, L. van Gool, M. Vergauwen, F. Verbiest, K. Cornelis, J. Tops, and R. Koch, "Visual Modeling with a Hand-Held Camera," Int'l J. Computer Vision, vol. 59, no. 3, pp. 207-232, 2004.
[19] H. Rushmeier and F. Bernardini, "Computing Consistent Normals and Colors from Photometric Data," Proc. Int'l Conf. 3-D Digital Imaging and Modeling, pp. 99-108, 1999.
[20] D. Scharstein and R. Szeliski, "High-Accuracy Stereo Depth Maps Using Structured Light," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 195-202, 2003.
[21] P. Sen, B. Chen, G. Garg, S. Marschner, M. Horowitz, M. Levoy, and H. Lensch, "Dual Photography," ACM Trans. Graphics, vol. 24, no. 3, pp. 745-755, 2005.
[22] P. Sturm, "Critical Motion Sequences for the Self-Calibration of Cameras and Stereo Systems with Variable Focal Length," Image and Vision Computing, vol. 20, nos. 5/6, pp. 415-426, 2002.
[23] P. Tan, S. Lin, and L. Quan, "Subpixel Photometric Stereo," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 8, pp. 1460-1471, Aug. 2008.
[24] T. Weise, B. Leibe, and L. van Gool, "Fast 3D Scanning with Automatic Motion Compensation," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007.
[25] R. Woodham, Y. Iwahori, and R. Barman, "Photometric Stereo: Lambertian Reflectance and Light Sources with Unknown Direction and Strength," Technical Report 91-18, Univ. of British Columbia, 1991.
[26] L. Zhang, B. Curless, A. Hertzmann, and S. Seitz, "Shape and Motion Under Varying Illumination: Unifying Structure from Motion, Photometric Stereo, and Multi-View Stereo," Proc. IEEE Int'l Conf. Computer Vision, pp. 618-625, 2003.
[27] L. Zhang, B. Curless, and S. Seitz, "Spacetime Stereo: Shape Recovery for Dynamic Scenes," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 367-374, 2003.
[28] T. Zickler, P. Belhumeur, and D. Kriegman, "Helmholtz Stereopsis: Exploiting Reciprocity for Surface Reconstruction," Proc. European Conf. Computer Vision, pp. 869-884, 2002.
[29] T. Zickler, P. Belhumeur, and D. Kriegman, "Toward a Stratification of Helmholtz Stereopsis," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 548-555, 2003.
[30] T. Zickler, "Reciprocal Image Features for Uncalibrated Helmholtz Stereopsis," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1801-1808, 2006.

Index Terms:
Digitization and image capture, scene analysis, geometric modeling.
Citation:
Daniel G. Aliaga, Yi Xu, "A Self-Calibrating Method for Photogeometric Acquisition of 3D Objects," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 4, pp. 747-754, April 2010, doi:10.1109/TPAMI.2009.202
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