The OU-ISIR Gait Database Comprising the Large Population Dataset and Performance Evaluation of Gait Recognition

被引：249
|
作者：
Iwama, Haruyuki [1 ]
Okumura, Mayu [1 ]
Makihara, Yasushi [1 ]
Yagi, Yasushi [1 ]
机构：
[1] Osaka Univ, Dept Intelligent Media, Inst Sci & Ind Res, Ibaraki, Osaka 5670047, Japan
来源：
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY | 2012年 / 7卷 / 05期
关键词：
Gait database; gait recognition; large population; performance evaluation; VIEW ANGLE; IMAGE; REPRESENTATION; TEMPLATE; QUALITY;
D O I：
10.1109/TIFS.2012.2204253
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
引用
收藏
页码：1511 / 1521
页数：11
相关论文
共 14 条
  • [1] OU-ISIR Wearable Sensor-based Gait Challenge: Age and Gender
    Thanh Trung Ngo
    Ahad, Md Atiqur Rahman
    Das Antar, Anindya
    Ahmed, Masud
    Muramatsu, Daigo
    Makihara, Yasushi
    Yagi, Yasushi
    Inoue, Sozo
    Flossain, Tahera
    Hattori, Yuichi
    2019 INTERNATIONAL CONFERENCE ON BIOMETRICS (ICB), 2019,
  • [2] Multi-view large population gait dataset and its performance evaluation for cross-view gait recognition
    Takemura N.
    Makihara Y.
    Muramatsu D.
    Echigo T.
    Yagi Y.
    IPSJ Transactions on Computer Vision and Applications, 2018, 10 (01)
  • [3] Multi-View Large Population Gait Database With Human Meshes and Its Performance Evaluation
    Li X.
    Makihara Y.
    Xu C.
    Yagi Y.
    IEEE Transactions on Biometrics, Behavior, and Identity Science, 2022, 4 (02): : 234 - 248
  • [4] CASIA-E: A Large Comprehensive Dataset for Gait Recognition
    Song, Chunfeng
    Huang, Yongzhen
    Wang, Weining
    Wang, Liang
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 45 (03) : 2801 - 2815
  • [5] Model-based gait recognition using graph network on very large population database
    Wang, Zhihao
    Tang, Chaoying
    Prasad, Shitala
    SSRN, 2022,
  • [6] The MMUISD Gait Database and Performance Evaluation Compared to Public Inertial Sensor Gait Databases
    Permatasari, Jessica
    Connie, Tee
    Song, Ong Thian
    COMPUTATIONAL SCIENCE AND TECHNOLOGY (ICCST 2019), 2020, 603 : 189 - 198
  • [7] Performance Analysis of Gait Recognition with Large Perspective Distortion
    Abdulsattar, Fatimah
    Carter, John
    2016 IEEE INTERNATIONAL CONFERENCE ON IDENTITY, SECURITY AND BEHAVIOR ANALYSIS (ISBA), 2016,
  • [8] Performance Evaluation of Model-Based Gait on Multi-View Very Large Population Database with Pose Sequences
    An W.
    Yu S.
    Makihara Y.
    Wu X.
    Xu C.
    Yu Y.
    Liao R.
    Yagi Y.
    IEEE Transactions on Biometrics, Behavior, and Identity Science, 2020, 2 (04): : 421 - 430
  • [9] An Evaluation Framework and Database for MoCap-Based Gait Recognition Methods
    Balazia, Michal
    Sojka, Petr
    REPRODUCIBLE RESEARCH IN PATTERN RECOGNITION, RRPR 2016, 2017, 10214 : 33 - 47
  • [10] The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication
    Thanh Trung Ngo
    Makihara, Yasushi
    Nagahara, Hajime
    Mukaigawa, Yasuhiro
    Yagi, Yasushi
    PATTERN RECOGNITION, 2014, 47 (01) : 228 - 237
12