TAIWAN – UNITED KINGDOM
COLLABORATION

Face recognition, gender recognition, age estimation, and expression recognition are commonly used to analyze face-related information. Among them, age estimation is the most difficult to utilize human's own vision. We can often easily determine the gender, expression, or whether a person is an acquaintance from a face, but we need to know the age of people we often meet by asking them, and we dare not easily check it visually, which indicates that it may be more difficult to estimate the age of a person by using a human face than by analyzing other face information. Although it is not easy to determine the exact age of a person with the naked eye, we can often point out a fairly accurate age range, so if we can learn more about how human vision determines and intercepts the age range, we may be able to improve the age estimation using machine vision. The following points are planned for this study:

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1. Create an accurate age estimator with machine vision, which is as good as the latest age estimators;

2. To design experiments to understand how human vision determines age and intercepts the age interval, and to explore how human vision can be utilized to improve the age estimation by machine vision;

3. To combine the individual strengths of the Taiwan and UK teams to investigate the effects of machine vision, human vision and wrinkle detection on age estimation and to improve the estimation performance;

4. To develop research projects with more application value and development potential to facilitate longer-term research and collaboration between the two organizations.