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.
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