Gait-based age estimation using a whole-generation gait database

Abstract

This paper addresses gait-based age estimation using a large-scale whole-generation gait database. Previous work on gait-based age estimation evaluated their methods using databases that included only 170 subjects at most with a limited age variation, which was insufficient to statistically demonstrate the possibility of gait-based age estimation. Therefore, we first constructed a much larger whole-generation gait database which includes 1,728 subjects with ages ranging from 2 to 94 years. We then provided a baseline algorithm for gait-based age estimation implemented by Gaussian process regression, which has achieved successes in the face-based age estimation field, in conjunction with silhouette-based gait features such as an averaged silhouette (or Gait Energy Image) which has been used extensively in many gait recognition algorithms. Finally, experiments using the whole-generation gait database demonstrated the viability of gait-based age estimation.