Facial Aging Databases, Techniques and Effects of Aging: A Survey
Citation
MLA Style: Mohammed Abdul Waheed , Ibtesaam Sanam "Facial Aging Databases, Techniques and Effects of Aging: A Survey" International Journal of Engineering Trends and Technology 67.10 (2019):8-13.
APA Style:Mohammed Abdul Waheed , Ibtesaam Sanam. Facial Aging Databases, Techniques and Effects of Aging: A Survey International Journal of Engineering Trends and Technology, 67(10),8-13.
Abstract
The facial aging databases promises results are shown on face recognition researches. Nevertheless, face recognition and retrieval across age remains tough and is still challenging. Facial aging represents the accumulation of changes over time Cross-Age Reference Coding (CARC) and a brand new big-scale dataset for face recognition and retrieval throughout age called Cross-Age Celebrity Dataset (CARD). One of the challenges in computerized face recognition is to achieve temporal invariance. In this Paper, we present a comprehensive evaluation of literature on cross age face recognition starting with the biological consequences of aging , it provides a survey of techniques, effects of aging on overall performance evaluation and facial aging databases. Evaluation of the impact of aging on the performance of age-invariant face recognition system is an vital measurement. We also study a 3D aging modelling technique for Face Recognition. It also presents a unique and efficient facial image representation primarily based on Local Binary Pattern (LBP) texture features.
Reference
[1] Lanitis A, Taylor CJ, Cootes TF (2002) Toward automatic simulation of aging effects on face images. IEEE Trans Pattern Anal Mach Intell.
[2] 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.
[3] X. Geng, Z.-H. Zhou, and K. Smith-Miles, “Automatic Age Estimation Based on Facial Aging Patterns,” IEEE Trans. Pattern Analysis and Machine Intelligence , Dec. 2007.
[4] Chen B, Chen C, Hsu W (2014) Cross-Age Celebrity Dataset (CACD).
[5] Best-Rowden L, Jain AK (2015) A longitudinal study of automatic face recognition .
[6] Li Z, Gong D, Li X, Tao D (2016) Aging face recognition: a hierarchical learning model based on local patterns selection. IEEE Trans Image Process.
[7] Xu C, Liu Q, Ye M (2017) Age invariant face recognition and retrieval by coupled auto encoder networks. Neurocomputing
[8] Geng X, Zhou Z-H, Smith-Miles K (2007) Automatic age estimation based on facial aging patterns. IEEE Trans Pattern Anal Mach Intell
[9] Jain, A.K., Klare, B., Park, U.: Face matching and retrieval in forensics applications. IEEE MultiMedia, 20 (2012)
[10] Kumar, N., Berg, A.C., Belhumeur, P.N., Nayar, S.K.: Attribute and simile classifiers for face verification (2009).
[11] Ahonen T, Hadid A, Pietikainen M (2006) Face description with local binary patterns: application to face recognition. IEEE Trans Pattern Anal Mach Intell.
[12] Chen, D., Cao, X., Wen, F., Sun, J.: Blessing of dimensionality: High-dimensional feature and its efficient compression for face verification. (2013).
[13] Albert AM, Ricanek K, Patterson E (2007) A review of the literature on the aging adult skull and face: implications for forensic science research and applications. Forensic Sci Int .
[14] N. Ramanathan, R. Chellappa, and S. Biswas. Computational methods for modeling facial aging 2009.
[15] 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.
[16] Singh M, Nagpal S, Singh R, Vatsa M (2014) On recognizing face images with weight and age variations.
[17] Wang, D., Hoi, S.C., He, Y., Zhu, J.: Retrieval-based face annotation by weak label regularized local coordinate coding. In: Proceedings of the 19th ACM international conference on ACM (2011)
[18] Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. Pattern Analysis and Machine Intelligence, IEEE Transactions on 31(2), 210{227 (2009)
[19] A. Lanitis, C.J. Taylor, and T.F. Cootes, “Toward Automatic Simulation of Aging Effects on Face Images,” Apr. 2002.
[20] Chen B-C, Chen C-S, Hsu WH (2014) Cross-age reference coding for age-invariant face recognition ,2013 .
Keywords
Face Recognition, Age invariant face recognition, 3D aging, Facial aging, Local binary pattern.