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Analysis on Age Invariance Face Recognition Study and Effects of Intrinsic and Extrinsic Factors on Skin Ageing

by Ashutosh Dhamija, R. B. Dubey
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 43
Year of Publication: 2019
Authors: Ashutosh Dhamija, R. B. Dubey
10.5120/ijca2019918527

Ashutosh Dhamija, R. B. Dubey . Analysis on Age Invariance Face Recognition Study and Effects of Intrinsic and Extrinsic Factors on Skin Ageing. International Journal of Computer Applications. 182, 43 ( Mar 2019), 1-9. DOI=10.5120/ijca2019918527

@article{ 10.5120/ijca2019918527,
author = { Ashutosh Dhamija, R. B. Dubey },
title = { Analysis on Age Invariance Face Recognition Study and Effects of Intrinsic and Extrinsic Factors on Skin Ageing },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2019 },
volume = { 182 },
number = { 43 },
month = { Mar },
year = { 2019 },
issn = { 0975-8887 },
pages = { 1-9 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number43/30434-2019918527/ },
doi = { 10.5120/ijca2019918527 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:14:06.792225+05:30
%A Ashutosh Dhamija
%A R. B. Dubey
%T Analysis on Age Invariance Face Recognition Study and Effects of Intrinsic and Extrinsic Factors on Skin Ageing
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 43
%P 1-9
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Currently, age invariance face recognition is an emerging research topic and has many potential applications. Face recognition under different intra-individual varieties, for example, demeanors, posture and impediment has been given satisfactory consideration in examination documented. In any case, age invariance confront acknowledgment still faces numerous difficulties because of age related natural changes in nearness of other appearance varieties. This paper studies noticeable distributed literary works to break down and outline work done as such far on age invariant face acknowledgment and to assess them on different scales like computational speed, precision, execution consistency in inborn outward conditions on skin maturing.

References
  1. Kumar, A. V. Srivastava and P. S. Yadav, Survey on age invariant facial recognition, Advances in Computer Science and Information Technology, vol. 2, no. 5, pp. 450-453, 2015.
  2. N. Ramanathan and R. Chellappa, Face verification across age progression, IEEE transactions on image processing, vol. 15, no. 11, 2006.
  3. H. Ling, S. Soatto, N. Ramanathan and DW. Jacobs, A study of face recognition as people age, IEEE International Conference on Computer Vision, pp. 1-8, 2007.
  4. N. R. Syambas and U. H. Purwant, Image processing and ace detection analysis on face verification based on age stages, 7th IEEE, Int. Conf. on Telecommunication Systems, Services and Applications, 2012.
  5. G. Mahalingam and C. Kambhamettu, Age invariant face recognition using graph Matching, Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), 2010
  6. S. Jyothi Nayak and M. Indiramma, Efficient face recognition with compensation for aging variations, IEEE 4th Int. Conf. on Advanced Computing, pp. 1-5, 2012.
  7. S. Jyothi Nayak, M Indiramma and N. Nagarathna , Modeling self–principal component analysis for age invariant face recognition, IEEE Int. Conf. on Computational Intelligence and Computing Research, 2012.
  8. Z. Li, U. Park, A. K. Jain., A discriminative model for age invariant face recognition, IEEE transactions on information forensics and security, vol.6, no.3, September 2011.
  9. A. Lanitis, A survey of effects of aging on biometric identity verification, International Journal of Biometrics ,vol. 2, pp. 34–52, 2009.
  10. A. Lanitis, CJ. Taylor and TF. Cootes, Toward automatic simulation of aging effects on face images, IEEE Trans Pattern Anal Mach Intell, vol. 24, pp. 442–455, 2002.
  11. N. Ramanathan, R. Chellappa and S. Biswas, Computational methods for modeling facial aging: a survey. J Vis Lang Comput, vol. 20, pp. 131–144, 2009.
  12. Y. Fu, G. Guo and TS. Huang, Age synthesis and estimation via faces: a survey, IEEE Trans Pattern Anal Mach Intell, vol. 32, pp. 1955–1976, 2010.
  13. A. Lanitis, C. Draganova and C. Christodoulou, Comparing different classifiers for automatic age estimation, IEEE Trans Syst Man Cybern B Cybern, vol. 34, pp. 621–628, 2004.
  14. K. Ricanek, A. Sethuram, EK. Patterson, AM. Albert and EJ. Boone, Craniofacial aging Wiley h and book of science and technology for homeland security, 2008.
  15. M. M. Sawant and K. M. Bhurch, Age invariance face recognition: a survey on facial aging databases, techniques and effect of aging, Artificial Intelligence Review, Springer, pp. 1-28, 13 October 2018.
  16. DW Thompson, On growth and form Cambridge, England, 191 7.
  17. L. Farkas, Anthropometry of head and face. Raven Press, New York, p XIX, 1994.
  18. L.G. Farkas and I.R. Munro, Anthropometric facial proportions in medicine. Charles C. Thomas, Springfield, 1987.
  19. N. Ramanathan, R. Chellappa and S. Biswas, Computational methods for modeling facial aging: a survey, Journal of Visual Languages and Computing, vol. 20, Issue 3, pp. 131-144, 2009.
  20. O. Friedman, Changes associated with aging face, Facial plastic surgery clinics of North America, vol. 13, Issue 3, pp. 371-380, 2005.
  21. W.F. Bergfeld, Aging skin., Int. J. Fertil. Womens Med,Vol. 42,pp. 57–66, 1997.
  22. M. P. Brincat, Y.M. Baron, and R. Galea, Estrogens and skin., Climateric vol. 8, pp. 110–123, 2005.
  23. M.K. Robinson, Population differences in skin structure and physiology and susceptibility to irritant and allergic contact dermatitis: implications for skin safety testing and risk assessment, Contact Derm. vol. 41, pp. 65–79, 1999.
  24. J.L. Rees, Genetics of sun sensitivity in humans, Am. J. Hum. Genet.vol. 75, pp. 739–751, 2004.
  25. B.A. Gilchrest, A review of skin aging and its medical therapy, Br. J. Dermatol. vol. 135, pp. 867–875, 1996.
  26. F. Martini, Fundamentals of anatomy and physiology, Benjamin-Cummings, San Francisco, 2004.
  27. K. M. Sudel, K. Venzke, Mielke, H. et al, Novel aspects of intrinsic and extrinsic aging of human skin: beneficial effects of soy extract, Photochem Photobiol, vol. 81, pp. 581–587, 2005.
  28. P.M. Elias, Stratum corneum architecture, metabolic activity and interactivity with subjacent cell layers, Exp. Dermatol. vol. 5, pp. 191–201 1996.
  29. M. Gray, Preventing and managing perinea dermatitis: a shared goal for wound and continence care, J. Wound Ostomy. Continence Nurs. vol. 31, pp. S2–S9, 2004.
  30. S. Neerken, G.W. Lucassen, M.A. Bisschop, E. Lender-ink, and T. A. Nuijs, Characterization of age-related effects in human skin: A comparative study that applies confocal laser scanning microscopy and optical coherence tomography, J. Biomed. Opt. vol 9, pp. 274– 281, 2004.
  31. M. Farage, and Maibach, H. (eds), Vulva: Anatomy, Physiology and Pathology. Informal Healthcare, New York, pp.27–42, 2006.
  32. J. M. Waller and H.I. Maibach, Age and skin structure and function, a quantitative approach (I): blood flow, pH, thickness, and ultrasound echo-genicity, Skin Res. Technol. vol. 11, pp. 221–235, 2005.
  33. G. Hall and T. J. Phillips, Estrogen and skin: effects of estrogen, menopause, and hormone replacement therapy on skin, J. Am. Acad. Dermatol, vol. 53, pp. 555–568, 2005.
  34. V. S. vrain, B.F and G. B , Biology of estrogens in skin: implications for skin aging, Exp. Dermatol, vol. 15, pp. 83–94 , 2006.
  35. G. K. Hall, andT. J. Phillips, Skin and hormone therapy, Clin.Obstet. Gynecol, vol. 47, pp. 437–449, 2004.
  36. N. J. Raine, Fenning, M.P. Brincat, and Y. Muscat-Baron, Skin aging and menopause implications for treatment, Am. J. Clin. Dermatol, vol. 4, pp. 371–378, 2003.
  37. M. J. Thornton, Biological actions of estrogens on skin, Exp. Dermatol, vol. 11, pp. 487–502, 2002.
  38. M. A. Farage, K.W. Miller, P. Elsner, and H. I. Maibach, Structural characteristics of aging skin: a review, J. Toxicol. Cutaneous Ocul.Toxicol, vol. 26, pp. 1–15, 2001.
  39. M. A. Farage, K.W. Miller, P. Elsner and H. I. Maibach, Functional and physiological characteristics of aging skin: a review, Aging clinical and experimental research, vol. 20, Issue 3, pp. 62–71, 2008.
  40. C. Castelo-Branco, F. Figueras, M. J. Martinez de Osaba, and J.A. Varnell, Facial wrinkling in postmeno-pausal women, Effects of smoking status and hormone replacement therapy, Maturitas, vol. 29, pp. 75–86, 1998.
  41. D. Wilhelm, P. Elsner, and H. I. Maibach, Standardized trauma (tape stripping) in human vulvar and forearm skin. Effects on transepidermal water loss, capacitance and pH, ActaDerm.Venereol, vol. 71, pp. 123–126, 1991.
  42. P. Elsner, D. Wilhelm and H.I. Maibach, Sodium lauryl sulfate-induced irritant contact dermatitis in vulvar and forearm skin of premenopausal and post-menopausal women, J. Am. Acad. Dermatol, vol. 23, pp. 648– 652, 1990.
  43. R. G. Glogau, Physiologic and structural changes associated with aging skin, Dermatol. Clin, vol. 15, pp. 555– 559, 1997.
  44. P. Marren, F. Wojnarowska and S. Powell, Allergic contact dermatitis and vulvar dermatoses, Br. J. Der-matol, vol. 126, pp. 52–56, 1992.
  45. N. A. Fenske and C.W. Lober, Structural and functional changes of normal aging skin, J. Amer. Acad. Dermatol, vol. 15, pp. 571–585, 1986.
  46. S. M. Jackson, M. L. Williams, K. R. Feingold, and P.M. Elias, Pathobiology of stratum corneum, West. J. Med., vol. 158, pp. 279–285, 1993.
  47. C. Kennedy, M. T. Bastiaens, C. D. Bajdik, et al., Lei-den Skin Cancer Study. Effect of smoking and sun on aging skin., J. Invest. Dermatol. vol. 120, pp. 548–554, 2003.
  48. Y. H. Leow, and H. I. Maibach, Cigarette smoking, cutaneous vasculature, and tissue oxygen, Clin.Der-matol., vol. 16, pp. 579–584, 1998.
  49. WebRef.org. [WEBSITE]. Available at: http:// www.webref.org/cancer/p/pack_year.htm, accessed on 2/27/06. Inverson Software Co.
  50. C. O. Barl and, E. Zettersten, B.S. Brown, J. Ye, P. M. Elias and R. Ghadially, Imiquimod-induced interleukin-1 alpha stimulation improves barrier homeostat is in aged murin epidermis, J. Invest. Derma-tol. vol. 122, pp. 330–336, 2004.
  51. S. Kang, J. H. Chung, J. H. Lee, G.J. Fisher, Y.S. Wan, E.A. Duell and J. J. Voorhees, Topical N-acetyl cysteine and genistein prevent ultraviolet-light-induced signaling that leads to photo aging in human skin in vivo, J. Invest. Dermatol, vol.120, pp. 835–841, 2003.
  52. K. Sauermann, S. Jaspers, U. Koop and H. Wenck, Topically applied vitamin C increases density of dermal papillae in aged human skin, BMC Dermatol. vol. 4, no.13, 2004.
  53. S Seite, C. Bredoux, , D. Compan, et al., Histological evaluation of a topically applied retinol-vitamin C combination. Skin, Pharmacol. Physiol. vol. 18, pp. 81–87, 2005.
  54. A. Sesto, M. Navarro, F. Burslem, and J. L. Jorcano, Analysis of ultraviolet B response in primary human keratinocytes using oligonucleotide micro-arrays, Proc. Natl Acad. Sci. U.S.A. vol. 99, pp. 2965–2970, 2002.
  55. M. A. Farage, K. W. Miller, P. Elsne and H. I. Maibach, Intrinsic and extrinsic factors in skin ageing: a review, International Journal of Cosmetic Science, vol. 30, pp. 87–95, 2008.
  56. Ming-Hsuan Yang, D. J. Kriegman and N. Ahuja, Detecting faces in images: A survey, IEEE Trans on Pattern Analysis and Machine Intelligence, vol. 24, no. 1, January 2002.
  57. M. Kirby and L. Sirovich, Application of Karhunen-Loeve procedure for characterization of human faces. IEEE Trans. Patt. Anal. Mach. Intell., vol. 12, no. 1, pp. 103-108, 1990.
  58. X. Li and S Areibi, A hardware/software code sign approach for face recognition,16th, International Conference on Microelectronics, Tunisia, 2004.
  59. Y. Taigman, M. Yang, M. Ranzato and L. Wolf, Deep face: Closing gap to human-level performance in face verification in CVPR, pp. 1701–1708, 2014.
  60. Y. Sun, Y. Chen, X. Wang and X. Tang, Deep learning face representation by joint identification-verification in advances in neural information processing systems, Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger, Eds., pp. 1988–1996, 2014.
  61. Z. Zhu, P. Luo, X. Wang and X. Tang, Deep learning identity preserving face space, in ICCV, pp. 113- 120, 2013.
  62. Y. Zhang, M. Shao, E. K. Wong and Y. Fu, Random faces guided sparse many-to-one encoder for pose-invariant face recognition, in ICCV, pp. 2416–2423, 2013.
  63. M. Kan, S. Shan, H. Chang, and X. Chen, Stacked progressive auto encoders (spae) for face recognition across poses, in CVPR, pp. 1883–1890, 2014.
  64. H. Zhai, C. Liu, H. Dong, Y. Ji, Y. Guo and S. Gong, Face verification across aging based on deep convolutional networks and local binary patterns, in International Conference Intelligence Science and Big Data Engineering, pp. 341–350, 2015.
  65. Y. Naik, Detailed survey of different face recognition approaches, International Journal of Computer Science and Mobile Computing, Vol.3, Issue.5, pp. 1306-1313, May- 2014.
  66. D. Sinha, J. P. Pandey and B. Chauhan, A deep learning approach for age invariance face recognition, International Journal of Pure and applied Mathematics, vol. 117, no. 21, pp. 371-389, 2017.
  67. Y. Wang, D. Gong, Z. Zhou, X. Ji, H. Wang, Z. L, W. Liu, T. Zhang, Orthogonal deep features decomposition for age-invariant face recognition, European Conference on Computer Vision, pp. 764-779, 2018.
  68. H. Zhou, K. M. Lam, Age-invariant face recognition based on identity inference from appearance age, Pattern recognition, vol. 76, pp. 191-202, 2018.
  69. W. Yitong, G. Dihong, Z. Zheng, J. Xing, W. Hao, Li Zhifeng, L Wei, and Z Tong, Orthogonal deep features decomposition for age-invariant face recognition, IEEE, Pattern Anal Mach Intell, vol. 29, pp. 2234–2240, 2018.
Index Terms

Computer Science
Information Sciences

Keywords

Age invariance PC vision outward conditions characteristic conditions maturing databases ageing skin intrinsic and extrinsic factors in skin ageing.

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