Work

The OU-ISIR Gait Database comprising the Large Population Dataset with Age and performance evaluation of age estimation

Year: 2017

Type: conference-abstract

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.

Source: IPSJ Transactions on Computer Vision and Applications

DOI: 10.1186/s41074-017-0035-2

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

Institutions: Nanjing University of Science and Technology, The University of Osaka

Language: English

Topic: Gait Recognition and Analysis

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $1,029