Title :
The OU-ISIR Gait Database Comprising the Large Population Dataset and Performance Evaluation of Gait Recognition
Author :
Iwama, Haruyuki ; Okumura, Mayu ; Makihara, Yasushi ; Yagi, Yasushi
Author_Institution :
Dept. of Intell. Media, Osaka Univ., Ibaraki, Japan
Abstract :
This paper describes the world´s largest gait database-the “OU-ISIR Gait Database, Large Population Dataset”-and its application to a statistically reliable performance evaluation of vision-based gait recognition. Whereas existing gait databases include at most 185 subjects, we construct a larger gait database that includes 4007 subjects (2135 males and 1872 females) with ages ranging from 1 to 94 years. The dataset allows us to determine statistically significant performance differences between currently proposed gait features. In addition, the dependences of gait-recognition performance on gender and age group are investigated and the results provide several novel insights, such as the gradual change in recognition performance with human growth.
Keywords :
biometrics (access control); computer vision; gait analysis; object recognition; performance evaluation; statistical analysis; visual databases; OU-ISIR gait database; biometric-based person-recognition techniques; large population dataset; performance evaluation; vision-based gait recognition; Cameras; Databases; Footwear; Legged locomotion; Performance evaluation; Reliability; Gait database; gait recognition; large population; performance evaluation;
Journal_Title :
Information Forensics and Security, IEEE Transactions on
DOI :
10.1109/TIFS.2012.2204253