3D Dense Correspondence for 3D Dense Morphable Face Shape Model
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3D Dense Correspondence for 3D Dense Morphable Face Shape Model

Authors: Tae in Seol, Sun-Tae Chung, Seongwon Cho

Abstract:

Realistic 3D face model is desired in various applications such as face recognition, games, avatars, animations, and etc. Construction of 3D face model is composed of 1) building a face shape model and 2) rendering the face shape model. Thus, building a realistic 3D face shape model is an essential step for realistic 3D face model. Recently, 3D morphable model is successfully introduced to deal with the various human face shapes. 3D dense correspondence problem should be precedently resolved for constructing a realistic 3D dense morphable face shape model. Several approaches to 3D dense correspondence problem in 3D face modeling have been proposed previously, and among them optical flow based algorithms and TPS (Thin Plate Spline) based algorithms are representative. Optical flow based algorithms require texture information of faces, which is sensitive to variation of illumination. In TPS based algorithms proposed so far, TPS process is performed on the 2D projection representation in cylindrical coordinates of the 3D face data, not directly on the 3D face data and thus errors due to distortion in data during 2D TPS process may be inevitable. In this paper, we propose a new 3D dense correspondence algorithm for 3D dense morphable face shape modeling. The proposed algorithm does not need texture information and applies TPS directly on 3D face data. Through construction procedures, it is observed that the proposed algorithm constructs realistic 3D face morphable model reliably and fast.

Keywords: 3D Dense Correspondence, 3D Morphable Face Shape Model, 3D Face Modeling.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1055863

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References:


[1] W. Zhao and R. Chellappa, Face Processing: Advanced Modeling and Methods, Elsevier, 2005.
[2] Y. Lee, D. Terzopuolos, K. Waters, "Realistic Modeling for Facial Animation", Proc. SIGGRAPH, Los Angeles, pp.55-61, August, 1995.
[3] F. I. Parke and K. Waters, "Appendix 1: Three-dimensional muscle model facial animation", Computer Facial Animation, A.K. Peters, Sept. 1996.
[4] F. Pighin, J. Hecker, D. Lischinski, R. Szeliski, and D. H. Salesin, "Synthesizing realistic facial expressions from photographs", In Computer Graphics, Annual Conference Series, SIGGRAPH, pp75-84, July, 1998.
[5] V. Blanz, T. Vetter, "A Morphable Model for the Synthesis of 3D Faces", Proc. of the SIGGRAPH'99, August 1999, Los Angeles, USA, pp.187-194, 1999.
[6] J. Ahlberg, "CANDIDE-3 -- an updated parameterized face", Report No. LiTH-ISY -R-2326, Dept. of Electrical Engineering, Linköping University, Sweden, 2001.
[7] R. L. Hsu, A. K. Jain, "Face Modeling for Recognition", Proc. Int'l Conf. Image Processing (ICIP), Vol.2, pp.693-696, 2001.
[8] A. Ansari and M. Abdel-Mottaleb, "3-D Face Modeling Using Two Views and a Generic Face Model with Application to 3-D Face Recognition", IEEE Conf. on Advanced Video and Signal Based Surveillance, pp.203-222, 2003.
[9] Y. Hu, D. Jiang, S. Yan, L. Zhang, H. zhang, "Automatic 3D reconstruction for face recognition", Proc. 6th IEEE Int'l Conf. on Automatic Face and Gesture Recognition, pp.843-848, 2004.
[10] H. Guo, J. Jiang and L. Zhang, "Building a 3D morphable face model by using thin plate splines for face reconstruction", LNCS Vol. 3338, pp.258-267, 2004.
[11] Z. Zhang, Z. Liu, D. Adler, M. F. Cohen, E. Hanson, and Y. Shan, "Robust and Rapid Generation of Animated Faces from Video Images: A Model-Based Modeling Approach", International Journal of Computer Vision, Vol.58, No.2, pp.93-119, June 2004.
[12] T. Russ, C. Boehnen, T. Peters, "3D Face Recognition Using 3D Alignment for PCA", IEEE Conf. on Computer Vision and Pattern Recognition, Vol.2, pp.1391-1398, 2006.
[13] Cyberware, http://www.cyberware.com/
[14] M. B. Stegmann, Mikkel B., Gomez, David Delgado: A Brief Introduction to Statistical Shape Analysis Technical University of Denmark, Lyngby, 2002.
[15] Besl, P. and McKay, N. "A Method for Registration of 3-D Shapes", Trans. PAMI, Vol. 14, No. 2, 1992.
[16] S. Rusinkewicz and M. Levoy, "Efficient Variants of the ICP Algorithm", Third International Conference on 3D Digital Imaging and Modeling, pp.145-152, June, 2001.
[17] B. Brown and S. Rusinkiewicz. "Non-Rigid Range-Scan Alignment Using Thin-Plate Splines", Symposium on 3D Data Processing. Visualization and Transmission, Vol.6, No.9, pp.759-765, September 2004.
[18] F. L. Bookstein., "Principal warps: Thin-plate splines and the decomposition of deforma tions", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.11, No.6, 567-585, June 1989.
[19] C. Brechbuhler, G. Gerig, G., O. Kubler, O.: "Parameterization of Closed Surfaces for 3-D Shape Description", Comp. Vision and Image Understanding, Vol.61, Issue.2, pp.154-170. 1995.
[20] R. Davies, C. Twining, T. Cootes, J. Waterton, and C. Taylor. "A minimum description length approach to statistical shape modeling", IEEE Transactions on Medical Imaging, Vol.5, Issue.5, pp.525-537, May 2002.