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Issue No.09 - Sept. (2013 vol.35)
pp: 2252-2269
D. Thomas , Nat. Inst. of Inf., Tokyo, Japan
A. Sugimoto , Nat. Inst. of Inf., Tokyo, Japan
ABSTRACT
Based on the spherical harmonics representation of image formation, we derive a new photometric metric for evaluating the correctness of a given rigid transformation aligning two overlapping range images captured under unknown, distant, and general illumination. We estimate the surrounding illumination and albedo values of points of the two range images from the point correspondences induced by the input transformation. We then synthesize the color of both range images using albedo values transferred using the point correspondences to compute the photometric reprojection error. This way allows us to accurately register two range images by finding the transformation that minimizes the photometric reprojection error. We also propose a practical method using the proposed photometric metric to register pairs of range images devoid of salient geometric features, captured under unknown lighting. Our method uses a hypothesize-and-test strategy to search for the transformation that minimizes our photometric metric. Transformation candidates are efficiently generated by employing the spherical representation of each range image. Experimental results using both synthetic and real data demonstrate the usefulness of the proposed metric.
INDEX TERMS
Lighting, Image color analysis, Harmonic analysis, Cost function, Geometry, Photometry,photometric reprojection, Range image, registration, photometry, spherical harmonics
CITATION
D. Thomas, A. Sugimoto, "Range Image Registration Using a Photometric Metric under Unknown Lighting", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.35, no. 9, pp. 2252-2269, Sept. 2013, doi:10.1109/TPAMI.2013.21
REFERENCES
[1] R. Basri and D. Jacobs, "Lambertian Reflectance and Linear Subspace," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 2, pp. 218-233, Feb. 2003.
[2] H. Bay, T. Tuytelaars, and L. van Gool, "SURF: Speeded Up Robust Features," Proc. European Conf. Computer Vision, pp. 404-417, 2006.
[3] P.J. Besl and N.D. McKay, "A Method for Registration of 3-D Shapes," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, Feb. 1992.
[4] D. Breitenreicher and C. Shnörr, "Intrinsic Second-Order Geometric Optimization for Robust Point Set Registration without Correspondence," Proc. Int'l Conf. Energy Minimization Methods in Computer Vision and Pattern Recognition, pp. 274-287, 2009.
[5] S. Choi, T. Kim, and Z. Yu, "Performance Evaluation of RANSAC Family," Proc. British Machine Vision Conf., 2009.
[6] P. Debevec, "Light Probe Image Gallery," http://ict.debevec.org/~debevecProbes/, 2004.
[7] O. Enqvist, F. Jiang, and F. Kahl, "A Brute-Force Algorithm for Reconstructing a Scene from Two Projections," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2011.
[8] B. Gutman, Y. Wang, T. Chan, P.M. Thompson, and A.W. Toga, "Shape Registration with Spherical Cross Correlation," Proc. MICCAI Workshop Math. Foundations of Computational Anatomy, pp. 56-67, 2008.
[9] P. Henry and M. Krainin, and E. Herbst, and X. Ren, and D. Fox, "RGB-D Mapping: Using Depth Cameras for Dense 2D Modeling of Indoor Environments," Proc. Int'l Symp. Experimental Robotics, 2010.
[10] B.K.P. Horn, "Closed-Form Solution of Absolute Orientation Using Orthonormal Matrices," J. Optical Soc. Am. A, vol. 5, no. 7, pp. 1127-1135, 1987.
[11] S. Izadi, D. Kim, O. Hilliges, D. Molyneaux, R. Newcombe, P. Kohli, J. Shotton, S. Hodges, D. Freeman, A. Davison, and A. Fitzgibbon, "Kinectfusion: Real-Time 3D Reconstruction and Interaction Using a Moving Depth Camera," Proc. ACM Symp. User Interface Software and Technology, 2011.
[12] B. Jian and B.C. Vemuri, "A Robust Algorithm for Point Set Registration Using Mixture of Gaussian," Proc. IEEE Int'l Conf. Computer Vision, vol. 2, pp. 1246-1251, 2005.
[13] A.E. Johnson and M. Hebert, "Surface Registration by Matching Oriented Points," Proc. IEEE Conf. 3-D Digital Imaging and Modeling, pp. 121-128, 1997.
[14] A.E. Johnson and S.B. Kang, "Registration and Integration of Textured 3D Data," Image and Vision Computing, vol. 17, no. 2, pp. 135-147, 1999.
[15] A. Lee, W. Sweldens, P. Shroder, L. Cowsar, and D. Dobkin, "MAPS: Multiresolution Adaptive Parameterization of Surfaces," Proc. ACM Siggraph, pp. 343-352, 1998.
[16] D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int'l J. Computer Vision, vol. 60, pp. 91-110, 2004.
[17] I.S. Okatani and A. Sugimoto, "Registration of Range Images that Preserves Local Surface Structure and Color," Proc. Int'l Symp. 3D Data Processing, Visualization and Transmission, pp. 786-796, 2004.
[18] C. Papazov and D. Burschka, "Stochastic Optimization for Rigid Point Set Registration," Proc. IEEE Int'l Symp. Visual Computing, pp. 1043-1054, 2009.
[19] R. Ramamoorthi, "Modeling Illumination Variation with Spherical Harmonics," Face Processing: Advanced Modeling Methods, pp. 385-424, Academic Press, 2006.
[20] S. Rusinkiewitcz and M. Leroy, "Efficient Variants of the ICP Algorithm," Proc. Int'l Conf. 3D Digital Imaging and Modeling, pp. 145-152, 2001.
[21] J.K. Seo, G.C. Sharp, and S.W. Lee, "Range Data Registration Using Photometric Features," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 1140-1145, 2005.
[22] T. Tachikawa, S. Hiura, and K. Sato, "Robust Estimation of Light Directions and Diffuse Reflectance of Known Shape Object," Proc. Vision, Modeling and Visualization Workshop, pp. 37-44, 2009.
[23] D. Thomas and A. Sugimoto, "Robustly Registering Range Images Using Local Distribution of Albedo," Computer Vision and Image Understanding, vol. 115, pp. 649-667, 2011.
[24] D. Thomas and A. Sugimoto, "Illumination-Free Photometric Metric for Range Image Registration," Proc. IEEE Workshop Applications of Computer Vision, pp. 97-104, 2012.
[25] A. Vedaldi, "SIFT Code for Matlab," http://www.vlfeat.org/~vedaldi/codesift.html , 2006.
[26] K. Zhou, H. Bao, and J. Shi, "3D Surface Filtering Using Spherical Harmonics," Computer Aided Design, vol. 36, pp. 363-375, 2004.
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