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The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication

Authors :
Thanh Trung Ngo
Yasuhiro Mukaigawa
Yasushi Makihara
Hajime Nagahara
Yasushi Yagi
Source :
Pattern Recognition. 47:228-237
Publication Year :
2014
Publisher :
Elsevier BV, 2014.

Abstract

This paper presents the largest inertial sensor-based gait database in the world, which is made open to the research community, and its application to a statistically reliable performance evaluation for gait-based personal authentication. We construct several datasets for both accelerometer and gyroscope of three inertial measurement units and a smartphone around the waist of a subject, which include at most 744 subjects (389 males and 355 females) with ages ranging from 2 to 78 years. The database has several advantages: a large number of subjects with a balanced gender ratio, variations of sensor types, sensor locations, and ground slope conditions. Therefore, we can reliably analyze the dependence of gait authentication performance on a number of factors such as gender, age group, sensor type, ground condition, and sensor location. The results with the latest existing authentication methods provide several insights for these factors. HighlightsWe present the world largest inertial sensor-based database to the community.Based on the database, females have a better recognition performance than males.People have the best recognition performance at their twenties.An accelerometer has a better recognition performance than a gyroscope.

Details

ISSN :
00313203
Volume :
47
Database :
OpenAIRE
Journal :
Pattern Recognition
Accession number :
edsair.doi...........54ef57bca1d7e894a8f12b491ae6f4c0
Full Text :
https://doi.org/10.1016/j.patcog.2013.06.028