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A Survey on Age Estimation Techniques

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Somy Soman, Amel Austine

Somy Soman and Amel Austine. A Survey on Age Estimation Techniques. International Journal of Computer Applications 161(4):26-28, March 2017. BibTeX

	author = {Somy Soman and Amel Austine},
	title = {A Survey on Age Estimation Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {161},
	number = {4},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {26-28},
	numpages = {3},
	url = {},
	doi = {10.5120/ijca2017913176},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Age is an important trait used for identity authentication. The factors that affect aging process include a person’s gene, health, living style etc. Age Estimation is predicting a person’s age. Out of these, face is the most convenient one. Age Estimation has lots of real-world applications, such as security control, biometrics, customer relationship management, entertainment and cosmetology. In this paper, we compare some of the techniques used in the age estimation based on face images. The most commonly used database is FG-NET. The most commonly used age estimation method is regression based because it takes into account the inter-relationship among the age values. Age Estimation via Grouping and Decision Fusion provides minimum MAE, 2.81 for FG-NET and 2.97 for MORPH II.


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