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

• DOI: 10.5281/zenodo.1055862
• Publication Date: 2008-05-23
• Authors: Seol, Tae In; Sun-Tae Chung; Seongwon Cho
• Keywords: 3D Face Modeling.; 0202 electrical engineering, electronic engineering, information engineering; 3D Morphable Face Shape Model; 02 engineering and technology; 3D Dense Correspondence

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.<br/>{"references": ["W. Zhao and R. Chellappa, Face Processing: Advanced Modeling and\nMethods, Elsevier, 2005.", "Y. Lee, D. Terzopuolos, K. Waters, \"Realistic Modeling for Facial\nAnimation\", Proc. SIGGRAPH, Los Angeles, pp.55-61, August, 1995.", "F. I. Parke and K. Waters, \"Appendix 1: Three-dimensional muscle model\nfacial animation\", Computer Facial Animation, A.K. Peters, Sept. 1996.", "F. Pighin, J. Hecker, D. Lischinski, R. Szeliski, and D. H. Salesin,\n\"Synthesizing realistic facial expressions from photographs\", In Computer\nGraphics, Annual Conference Series, SIGGRAPH, pp75-84, July, 1998.", "V. Blanz, T. Vetter, \"A Morphable Model for the Synthesis of 3D Faces\",\nProc. of the SIGGRAPH'99, August 1999, Los Angeles, USA, pp.187-194,\n1999.", "J. Ahlberg, \"CANDIDE-3 -- an updated parameterized face\", Report No.\nLiTH-ISY -R-2326, Dept. of Electrical Engineering, Link\u00f6ping\nUniversity, Sweden, 2001.", "R. L. Hsu, A. K. Jain, \"Face Modeling for Recognition\", Proc. Int'l Conf.\nImage Processing (ICIP), Vol.2, pp.693-696, 2001.", "A. Ansari and M. Abdel-Mottaleb, \"3-D Face Modeling Using Two Views\nand a Generic Face Model with Application to 3-D Face Recognition\",\nIEEE Conf. on Advanced Video and Signal Based Surveillance,\npp.203-222, 2003.", "Y. Hu, D. Jiang, S. Yan, L. Zhang, H. zhang, \"Automatic 3D\nreconstruction for face recognition\", Proc. 6th IEEE Int'l Conf. on\nAutomatic Face and Gesture Recognition, pp.843-848, 2004.\n[10] H. Guo, J. Jiang and L. Zhang, \"Building a 3D morphable face model by\nusing thin plate splines for face reconstruction\", LNCS Vol. 3338,\npp.258-267, 2004.\n[11] Z. Zhang, Z. Liu, D. Adler, M. F. Cohen, E. Hanson, and Y. Shan, \"Robust\nand Rapid Generation of Animated Faces from Video Images: A\nModel-Based Modeling Approach\", International Journal of Computer\nVision, Vol.58, No.2, pp.93-119, June 2004.\n[12] T. Russ, C. Boehnen, T. Peters, \"3D Face Recognition Using 3D\nAlignment for PCA\", IEEE Conf. on Computer Vision and Pattern\nRecognition, Vol.2, pp.1391-1398, 2006.\n[13] Cyberware, http://www.cyberware.com/\n[14] M. B. Stegmann, Mikkel B., Gomez, David Delgado: A Brief Introduction\nto Statistical Shape Analysis Technical University of Denmark, Lyngby,\n2002.\n[15] Besl, P. and McKay, N. \"A Method for Registration of 3-D Shapes\", Trans.\nPAMI, Vol. 14, No. 2, 1992.\n[16] S. Rusinkewicz and M. Levoy, \"Efficient Variants of the ICP Algorithm\",\nThird International Conference on 3D Digital Imaging and Modeling,\npp.145-152, June, 2001.\n[17] B. Brown and S. Rusinkiewicz. \"Non-Rigid Range-Scan Alignment Using\nThin-Plate Splines\", Symposium on 3D Data Processing. Visualization\nand Transmission, Vol.6, No.9, pp.759-765, September 2004.\n[18] F. L. Bookstein., \"Principal warps: Thin-plate splines and the\ndecomposition of deforma tions\", IEEE Transactions on Pattern Analysis\nand Machine Intelligence, Vol.11, No.6, 567-585, June 1989.\n[19] C. Brechbuhler, G. Gerig, G., O. Kubler, O.: \"Parameterization of Closed\nSurfaces for 3-D Shape Description\", Comp. Vision and Image\nUnderstanding, Vol.61, Issue.2, pp.154-170. 1995.\n[20] R. Davies, C. Twining, T. Cootes, J. Waterton, and C. Taylor. \"A\nminimum description length approach to statistical shape modeling\", IEEE\nTransactions on Medical Imaging, Vol.5, Issue.5, pp.525-537, May 2002."]}<br/>