Computational methods for modeling facial aging: A survey

Facial aging, a new dimension that has recently been added to the problem of face recognition, poses interesting theoretical and practical challenges to the research community. The problem which originally generated interest in the psychophysics and human perception community has recently found enhanced interest in the computer vision community. How do humans perceive age? What constitutes an age-invariant signature that can be derived from faces? How compactly can the facial growth event be described? How does facial aging impact recognition performance? In this paper, we give a thorough analysis on the problem of facial aging and further provide a complete account of the many interesting studies that have been performed on this topic from different fields. We offer a comparative analysis of various approaches that have been proposed for problems such as age estimation, appearance prediction, face verification, etc. and offer insights into future research on this topic.

[1]  A.J O'Toole,et al.  3D shape and 2D surface textures of human faces: the role of "averages" in attractiveness and age , 1999, Image Vis. Comput..

[2]  Yun Fu,et al.  Human Age Estimation With Regression on Discriminative Aging Manifold , 2008, IEEE Transactions on Multimedia.

[3]  Zhi-Hua Zhou,et al.  Automatic Age Estimation Based on Facial Aging Patterns , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  L. Farkas,et al.  Anthropometric Facial Proportions in Medicine , 1986 .

[5]  Rama Chellappa,et al.  Face Processing: Advanced Modeling and Methods , 2006, J. Electronic Imaging.

[6]  J. B. Pittenger,et al.  Aging faces as viscal-elastic events: implications for a theory of nonrigid shape perception. , 1975, Journal of experimental psychology. Human perception and performance.

[7]  R. Chellappa,et al.  A Non-generative Approach for Face Recognition Across Aging , 2008, 2008 IEEE Second International Conference on Biometrics: Theory, Applications and Systems.

[8]  Haizhou Ai,et al.  Demographic Classification with Local Binary Patterns , 2007, ICB.

[9]  D. Perrett,et al.  Perception of age in adult Caucasian male faces: computer graphic manipulation of shape and colour information , 1995, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[10]  K. Ricanek,et al.  Aspects of Age Variation in Facial Morphology Affecting Biometrics , 2007, 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems.

[11]  Rama Chellappa,et al.  Modeling shape and textural variations in aging faces , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[12]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[13]  Hong Chen,et al.  A high resolution grammatical model for face representation and sketching , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[14]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[15]  C. Christodoulou,et al.  Comparing different classifiers for automatic age estimation , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[16]  Klara Nahrstedt,et al.  Proceedings of the 24th ACM international conference on Multimedia , 2006, MM 2006.

[17]  Stefano Soatto,et al.  A Study of Face Recognition as People Age , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[18]  Karl Ricanek,et al.  MORPH: a longitudinal image database of normal adult age-progression , 2006, 7th International Conference on Automatic Face and Gesture Recognition (FGR06).

[19]  V. Bruce,et al.  Further experiments on the perception of growth in three dimensions , 1989, Perception & psychophysics.

[20]  Niels da Vitoria Lobo,et al.  Age classification from facial images , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[21]  J. B. Pittenger,et al.  Perceptual information for the age level of faces as a higher order invariant of growth. , 1979, Journal of experimental psychology. Human perception and performance.

[22]  Anil K. Jain,et al.  Handbook of Face Recognition, 2nd Edition , 2011 .

[23]  Timothy F. Cootes,et al.  Active Appearance Models , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Yu Zhang,et al.  Learning from facial aging patterns for automatic age estimation , 2006, MM '06.

[25]  Bernard Tiddeman,et al.  Towards Realism in Facial Image Transformation: Results of a Wavelet MRF Method , 2005, Comput. Graph. Forum.

[26]  Bernard Tiddeman,et al.  Prototyping and Transforming Facial Textures for Perception Research , 2001, IEEE Computer Graphics and Applications.

[27]  J T Todd,et al.  Perception of growth: a geometric analysis of how different styles of change are distinguished. , 1981, Journal of experimental psychology. Human perception and performance.

[28]  Rama Chellappa,et al.  Modeling Age Progression in Young Faces , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[29]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression Database , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[30]  Timothy F. Cootes,et al.  Toward Automatic Simulation of Aging Effects on Face Images , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Hyeonjoon Moon,et al.  The FERET Evaluation Methodology for Face-Recognition Algorithms , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  J. B. Pittenger,et al.  Wrinkling and head shape as coordinated sources of age-level information , 1980 .

[33]  Song-Chun Zhu,et al.  A Multi-Resolution Dynamic Model for Face Aging Simulation , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[34]  D'arcy W. Thompson.  On growth and form i , 1943 .

[35]  J T Todd,et al.  The perception of growth in three dimensions , 1983, Perception & psychophysics.

[36]  Matti Pietikäinen,et al.  Face Description with Local Binary Patterns: Application to Face Recognition , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[37]  Yiying Tong,et al.  Face recognition with temporal invariance: A 3D aging model , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

[38]  J. B. Pittenger,et al.  The perception of human growth. , 1980, Scientific American.

[39]  Yun Fu,et al.  Image-Based Human Age Estimation by Manifold Learning and Locally Adjusted Robust Regression , 2008, IEEE Transactions on Image Processing.

[40]  Christopher M. Bishop,et al.  Pattern Recognition and Machine Learning (Information Science and Statistics) , 2006 .

[41]  Maulin R. Gandhi.  A Method for Automatic Synthesis of Aged Human Facial Images , 2004 .

[42]  A. O'Toole,et al.  Three-Dimensional Caricatures of Human Heads: Distinctiveness and the Perception of Facial Age , 1997, Perception.

[43]  R. Shaw,et al.  The role of symmetry in event perception. , 1974 .

[44]  Melvin L. Moss,et al.  The human face—An account of the postnatal growth and development of the craniofacial skeleton , 1971 .

[45]  Rama Chellappa,et al.  Face Verification Across Age Progression , 2006, IEEE Transactions on Image Processing.

[46]  C. Cacou.  Anthropometry of the head and face , 1995 .