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Issue No.05 - May (2010 vol.32)
pp: 947-954
Unsang Park , Michigan State University, East Lansing
Yiying Tong , Michigan State University, East Lansing
Anil K. Jain , Michigan State University, East Lansing
One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.
Face recognition, facial aging, aging modeling, aging simulation, 3D face model.
Unsang Park, Yiying Tong, Anil K. Jain, "Age-Invariant Face Recognition", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.32, no. 5, pp. 947-954, May 2010, doi:10.1109/TPAMI.2010.14
[1] U. Park, Y. Tong, and A.K. Jain, "Face Recognition with Temporal Invariance: A 3D Aging Model," Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 1-7, 2008.
[2] P.J. Phillips, W.T. Scruggs, A.J. O'Toole, P.J. Flynn, K.W. Bowyer, C.L. Schott, and M. Sharpe, "FRVT 2006 and ICE 2006 Large-Scale Results," Technical Report NISTIR 7408, Nat'l Inst. of Standards and Technology, Mar. 2007.
[3] N. Ramanathan and R. Chellappa, "Modeling Age Progression in Young Faces," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 387-394, 2006.
[4] A. Lanitis, C.J. Taylor, and T.F. Cootes, "Toward Automatic Simulation of Aging Effects on Face Images," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 4, pp. 442-455, Apr. 2002.
[5] X. Geng, Z.-H. Zhou, and K. Smith-Miles, "Automatic Age Estimation Based on Facial Aging Patterns," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 29, no. 7, pp. 2234-2240, Dec. 2007.
[6] J. Wang, Y. Shang, G. Su, and X. Lin, "Age Simulation for Face Recognition," Proc. Int'l Conf. Pattern Recognition, pp. 913-916, 2006.
[7] E. Patterson, K. Ricanek, M. Albert, and E. Boone, "Automatic Representation of Adult Aging in Facial Images," Proc. Int'l Conf. Visualization, Imaging, and Image Processing, pp. 171-176, 2006.
[8] H. Ling, S. Soatto, N. Ramanathan, and D. Jacobs, "A Study of Face Recognition as People Age," Proc. IEEE Int'l Conf. Computer Vision, pp. 1-8, 2007.
[9] N. Ramanathan and R. Chellappa, "Face Verification Across Age Progression," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 462-469, 2005.
[10] D.W. Thompson, On Growth and Form. Dover Publications, 1992.
[11] J.B. Pittenger and R.E. Shaw, "Aging Faces as Viscal-Elastic Events: Implications for a Theory of Nonrigid Shape Perception," J. Experimental Psychology: Human Perception and Performance, vol. 1, pp. 374-382, 1975.
[12] A. O'Toole, T. Vetter, H. Volz, and E. Salter, "Three-Dimensional Caricatures of Human Heads: Distinctiveness and the Perception of Facial Age," Perception, vol. 26, pp. 719-732, 1997.
[13] J. Suo, F. Min, S. Zhu, S. Shan, and X. Chen, "A Multi-Resolution Dynamic Model for Face Aging Simulation," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 1-8, 2007.
[14] A. Lanitis, C. Draganova, and C. Christodoulou, "Comparing Different Classifiers for Automatic Age Estimation," IEEE Trans. Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 34, no. 1, pp. 621-628, Feb. 2004.
[15] K. Scherbaum, M. Sunkel, H.-P. Seidel, and V. Blanz, "Prediction of Individual Non-Linear Aging Trajectories of Faces," Computer Graphics Forum, vol. 26, no. 3, pp. 285-294, 2007.
[16] "FaceVACS Software Developer Kit, Cognitec Systems GmbH," http:/, 2010.
[17] M.B. Stegmann, "The AAM-API: An Open Source Active Appearance Model Implementation," Proc. Int'l Conf. Medical Image Computing and Computer-Assisted Intervention, pp. 951-952, 2003.
[18] T.F. Cootes, G.J. Edwards, and C.J. Taylor, "Active Appearance Models," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 6, pp. 681-685, June 2001.
[19] V. Blanz and T. Vetter, "A Morphable Model for the Synthesis of 3D Faces," Proc. ACM SIGGRAPH Conf. Computer Graphics and Interactive Techniques, pp. 187-194, 1999.
[20] F. Pighin, R. Szeliski, and D.H. Salesin, "Modeling and Animating Realistic Faces from Images," Int'l J. Computer Vision, vol. 50, no. 2, pp. 143-169, 2002.
[21] A. Albert, K. Ricanek, and E. Patterson, "The Aging Adult Skull and Face: A Review of the Literature and Report on Factors and Processes of Change," UNCW Technical Report WRG FSC-A, 2004.
[22] Anthropometry of the Head and Face, L.G. Farkas, ed. Lippincott Williams & Wilkins, 1994.
[23] "FG-NET Aging Database," http:/, 2010.
[24] K.J. Ricanek and T. Tesafaye, "Morph: A Longitudinal Image Database of Normal Adult Age-Progression," Proc. Int'l Conf. Automatic Face and Gesture Recognition, pp. 341-345, 2006.
[25] N. Nixon and P. Galassi, The Brown Sisters, Thirty-Three Years. The Museum of Modern Art, 2007.
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