What is an Age Identifier?
An age identifier is a computer vision technology that can determine a person’s age based on biometric features. Although age estimation can be accomplished using different biometric traits, this article is focused on facial age estimation. Facial age estimation relies on biometric features extracted from a person’s face. In automatic facial age identification, the aim is to use dedicated algorithms that enable the estimation of a person’s age based on features derived from his/her face image.
How does Age Identification work?
A person’s age can be identified by using face analysis technology. To estimate an accurate age or age group of a facial image, the face analysis algorithm requires a huge data set of faces attached with age labels. The technology extracts information from photographs and maps out a series of facial landmarks. These include the location of the pupils, corners of the eye, boundaries of the lips, and the edges of the eyebrows. By analyzing these facial landmarks, face analysis programs can estimate the age, as well the gender of a person.
How can age identifier be applied?
The need for age identification technology comes from the fact that humans are not always good at estimating a person’s age. For business, this is often a challenge and the reason why ID is required. For example, even the most experienced bouncer may struggle to distinguishing between a 17-year-old and an 18-year-old if they don’t have any form of ID on them. To combat this problem, businesses have come to rely on automatic facial age identification.
The process of age identification could figure in a variety of applications ranging from access control, human machine interaction, person identification and data mining and organization. Typical applications for each category mentioned above include:
Age-based access control:
This refers to age-based access restrictions and apply to physical and virtual access premises. For example, business may want to restrict access to section of a building, web pages, or even prevent the purchase of certain goods by under aged individuals (alcohol or cigarettes). Automatic facial age identification can also be applied to provide objective, accurate and non-invasive determination of the age of a person seeking access to a specific physical or virtual domain.
Age adaptive human machine interaction:
People tend to interact with technology (computers or machines) differently, depending on their age. As a result, there are different requirements and needs for each age group. Automatic age identification can be applied to such technologies to determine the age group the user falls under. The content and user interface can therefore be adjusted to meet the needs of the determined age group. For example, icon-based interfaces can be activated for young children whereas text with large font can be activated when dealing with older users. Age adaptive HCI is particularly useful for publicly available resources such as information kiosks.
Age invariant person identification:
Age invariant identity verification can be developed by applying age progression techniques for deforming the face of a subject in order to predict how the subject will look like in the future. Age progression algorithms often require information related to the current age of a person, hence an accurate facial age estimation system can play a key role in developing automatic age progression systems, supporting in that way age-invariant identity verification.
Data mining and organization:
Age estimation systems can be used for age-based retrieval and classification of face images enabling in that way automatic sorting and image retrieval from e-photo albums and the internet.