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

• Published in: Pattern recognition Vol. 47; no. 1; pp. 228 - 237
• Main Authors: Ngo, Thanh Trung, Makihara, Yasushi, Nagahara, Hajime, Mukaigawa, Yasuhiro, Yagi, Yasushi
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.01.2014; Elsevier
• Subjects: Age; Applied sciences; Authentication; Cryptography; Exact sciences and technology; Gait; Gait-based owner authentication; Grounds; Inertial; Inertial sensor; Information, signal and communications theory; Large-scale database; Performance evaluation; Sensors; Signal and communications theory; Telecommunications and information theory; Performance evaluation; Inertial sensor; Large-scale database; Gait-based owner authentication; Range finding; Ground based measurement; Measurement sensor; Sex; Statistical method; Authentication; Database; Gyroscope; Localization; Smartphone
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2013.06.028

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. •We 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.