Credit: Public Domain Computerised face recognition is an important part of initiatives to develop security systems, in building social networks, in curating photographs, and many other applications. Systems that allow a computer to estimate with precision a person's age based on an analysis of their face are discussed in the International Journal of Applied Pattern Recognition.
Jayant Jagtap and Manesh Kokare of the Department of Electronics and Telecommunication Engineering, at the Shri Guru Gobind Singhji Institute of Engineering and Technology, in Vishnupuri, Nanded, India, suggest that age classification adds a useful layer to such security systems, customer relationship management, and of course for surveillance. The team has carried out a detailed survey of age classification systems to reveal the pros and cons of each and to point new research in the right direction for the development of an even more accurate algorithm than any that currently exists. Indeed, their survey reveals that despite the best efforts of developers there is no real-time highly accurate algorithm for age classification yet in existence. The existing age classification systems commonly use geometric ratios of facial features and analysis of wrinkles in the skin.
One of the problems facing developers of such a tool is that databases containing images of a person's face tend not to accumulate images at different ages. This limits how well an algorithm might be trained based on a database of photos at known ages. While there are many serious tools and many spurious or fun tools available on the internet, there are no public systems that allow a computer to guess how old you are with useful accuracy. This may well be a positive point to make from the personal privacy point of view but not for the wider implications of face recognition and age categorization.
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More information: Jayant Jagtap et al. Human age classification via face images: a survey, International Journal of Applied Pattern Recognition (2017). DOI: 10.1504/IJAPR.2017.086594
