The ou-isir gait database comprising the large population dataset with age and performance evaluation of age estimation

Chi Xu, Yasushi Makihara, Gakuto Ogi, Xiang Li, Yasushi Yagi, Jianfeng Lu

Abstract:

In this paper, we describe the world’s largest gait database, the “OU-ISIR Gait Database, Large Population Dataset with
Age (OULP-Age)” and its application to a statistically reliable performance evaluation of gait-based age estimation.
Whereas existing gait databases include only 4016 subjects at most, we constructed an extremely large-scale gait
database that includes 63,846 subjects (31,093 males and 32,753 females) with ages ranging from 2 to 90 years old.
Benchmark algorithms of gait-based age estimation were then implemented to evaluate statistically significant
performance differences. Additionally, the dependence of gait-based age estimation performance on gender and age
group, in addition to the number of training subjects, was investigated to provide several insights for future research
on the topic.