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

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 gyro...

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Veröffentlicht in:	Pattern recognition Jg. 47; H. 1; S. 228 - 237
Hauptverfasser:	Ngo, Thanh Trung, Makihara, Yasushi, Nagahara, Hajime, Mukaigawa, Yasuhiro, Yagi, Yasushi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier Ltd 01.01.2014 Elsevier
Schlagworte:	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
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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. •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.
AbstractList	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. 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.
Author	Ngo, Thanh Trung Makihara, Yasushi Yagi, Yasushi Nagahara, Hajime Mukaigawa, Yasuhiro
Author_xml	– sequence: 1 givenname: Thanh Trung surname: Ngo fullname: Ngo, Thanh Trung email: trung@am.sanken.osaka-u.ac.jp, trungbeo@gmail.com organization: The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan – sequence: 2 givenname: Yasushi surname: Makihara fullname: Makihara, Yasushi email: makihara@am.sanken.osaka-u.ac.jp organization: The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan – sequence: 3 givenname: Hajime surname: Nagahara fullname: Nagahara, Hajime email: nagahara@limu.ait.kyushu-u.ac.jp organization: Faculty of Information Science and Electrical Engineering, Kyushu University, 744, Motooka, Nishiku, Fukuoka 819-0395, Japan – sequence: 4 givenname: Yasuhiro surname: Mukaigawa fullname: Mukaigawa, Yasuhiro email: mukaigaw@am.sanken.osaka-u.ac.jp organization: The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan – sequence: 5 givenname: Yasushi surname: Yagi fullname: Yagi, Yasushi email: yagi@am.sanken.osaka-u.ac.jp organization: The Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan
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Cites_doi	10.1007/978-3-642-17610-4_20 10.1109/ICASSP.2011.5947150 10.1109/34.667881 10.1109/BTAS.2012.6374552 10.1117/12.603331 10.1016/j.patcog.2010.04.019 10.1007/3-540-44887-X_82 10.1109/ICBBE.2007.142 10.1109/TFUZZ.2011.2171973 10.1109/AUTOID.2007.380623 10.1109/IIHMSP.2010.84 10.1109/BTAS.2007.4401905 10.1023/A:1019154432472 10.1155/2009/415817 10.1109/ICB.2012.6199833 10.1007/11748625_12 10.1109/WAINA.2010.145 10.1109/IJCB.2011.6117527 10.1109/ICASSP.2005.1415569 10.1016/j.patrec.2008.08.002 10.1007/978-3-642-19318-7_52 10.1109/IIHMSP.2010.83 10.1109/ICIEA.2007.4318894 10.1016/j.patcog.2010.01.017 10.1109/BTAS.2010.5634532 10.1109/TIFS.2007.902030 10.1109/ROBOT.2007.364224
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Keywords	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
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References	Lipkus (bib36) 2006; 26 Yang, Wang, Chen (bib1) 2008; 29 Cook, Das (bib4) 2004 Gafurov, Helkala, Sondrol (bib10) 2006 Gafurov, Snekkenes, Bours (bib23) 2007; 2 C. Nickel, H. Brandt, C. Busch, Classification of acceleration data for biometric gait recognition on mobile devices, in: BIOSIG, 2011, pp. 57–66. J.R. Kwapisz, G.M. Weiss, S.A. Moore, Cell phone based biometric identification, in: IEEE Fourth International Conference on Biometrics: Theory, Applications and Systems, 2010, pp. 1–7. P. Phillips, D. Blackburn, M. Bone, P. Grother, R. Micheals, E. Tabassi, Face recognition vendor test Snedecor, Cochran (bib38) 1967 Gafurov, Snekkenes (bib11) 2009; 2009 J. Mantyjarvi, M. Lindholm, E. Vildjiounaite, S.-M. Makela, H. Ailisto, Identifying users of portable devices from gait pattern with accelerometers, in: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 2, 2005, pp. 973–976. B. Huang, M. Chen, P. Huang, Y. Xu, Gait modeling for human identification, in: IEEE International Conference on Robotics and Automation, 2007, pp. 4833–4838. In Japanese. A. Kale, N. Cuntoor, B. Yegnanarayana, A. Rajagopalan, R. Chellappa, Gait analysis for human identification, in: Audio– and Video–Based Biometric Person Authentication LNCS, 2003, pp. 706–714. Alvarez-Alvarez, Trivino, Cordon (bib19) 2012; 20 L. Rong, Z. Jianzhong, L. Ming, H. Xiangfeng, A wearable acceleration sensor system for gait recognition, in: 2nd IEEE Conference on Industrial Electronics and Applications, 2007, pp. 2654–2659. M.O. Derawi, P. Bours, K. Holien, Improved cycle detection for accelerometer based gait authentication, in: Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010, pp. 312–317. E. Vildjiounaite, S.-M. Makela, M. Lindholm, R. Riihimaki, V. Kyllonen, J. Mantyjarvi, H. Ailisto, Unobtrusive multimodal biometrics for ensuring privacy and information security with personal devices, in: 4th International Conference on Pervasive Computing, PERVASIVE, 2006, pp. 187–201. D. Gafurov, E. Snekkenes, P. Bours, Improved gait recognition performance using cycle matching, in: 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops (WAINA), 2010, pp. 836–841. D. Gafurov, Security analysis of impostor attempts with respect to gender in gait biometrics, in: First IEEE International Conference on Biometrics: Theory, Applications, and Systems, 2007, pp. 1–6. Kionic Inc., KXTF9 S. Bonnet, P. Jallon, Hidden markov models applied onto gait classification, in: 18th European Signal Processing Conference (EUSIPCO-2010), 2010, pp. 929–933. F. Juefei-Xu, C. Bhagavatula, A. Jaech, U. Prasad, M. Savvides, Gait-id on the move: pace independent human identification using cell phone accelerometer dynamics, in: IEEE 5th International Conference on Biometrics, 2012, pp. 8–15. J.C. Augusto, C.D. Nugent, A new architecture for smart homes based on ADB and temporal reasoning, in: Toward a Human Friendly Assistive Environment, Proceedings of 2nd International Conference On Smart homes and health Telematic, ICOST2004, 2004, pp. 106–113. L. Rong, D. Zhiguo, Z. Jianzhong, L. Ming, Identification of individual walking patterns using gait acceleration, in: The 1st International Conference on Bioinformatics and Biomedical Engineering, 2007, pp. 543–546. H.J. Ailisto, M. Lindholm, J. Mantyjarvi, E. Vildjiounaite, S. Makela, Identifying people from gait pattern with accelerometers, in: Biometric Technology for Human Identification, SPIE, vol. 5779, 2005, pp. 7–14. D. Gafurov, P. Bours, Improved hip based individual recognition using wearable motion recording sensor, in: Security Technology, Disaster Recovery and Business Continuity, vol. 122, Communications in Computer and Information Science, Springer, Berlin, Heidelberg, 2010, pp. 179–186. . D. Gafurov, E. Snekkenes, P. Bours, Gait authentication and identification using wearable accelerometer sensor, in: 5th IEEE Workshop on Automatic Identification Advanced Technologies, 2007, pp. 220–225. ZMP Inc., IMUZ Trivino, Alvarez-Alvarez, Bailador (bib18) 2010; 43 Y. Makihara, N.T. Trung, H. Nagahara, R. Sagawa, Y. Mukaigawa, Y. Yagi, Phase registration of a single quasi-periodic signal using self dynamic time warping, in: The Tenth Asian Conference on Computer Vision, Springer-Verlag, 2010, pp. 667–678. D. Gafurov, Performance and Security Analysis, Ph.D. Thesis, Faculty of Mathematics and Natural Sciences at the University of Oslo, 2008. Altun, Barshan, Tunçel (bib2) 2010; 43 M.O. Derawi, C. Nickely, P. Bours, C. Busch, Unobtrusive user-authentication on mobile phones using biometric gait recognition, in: 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010, pp. 306–311. N. Trung, Y. Makihara, H. Nagahara, R. Sagawa, Y. Mukaigawa, Y. Yagi, Phase registration in a gallery improving gait authentication, in: International Joint Conference on Biometrics (IJCB2011), IEEE and IAPR, 2011, pp. 1–7. Kittler, Hatef, Duin, Matas (bib35) 1998; 20 2002. N. Trung, Y. Makihara, H. Nagahara, Y. Mukaigawa, Y. Yagi, Performance evaluation of gait recognition using the largest inertial sensor-based gait database, in: Proceedings of the 5th IAPR International Conference on Biometrics, 2012, pp. 360–366. T. Kobayashi, K. Hasida, N. Otsu, Rotation invariant feature extraction from 3-D acceleration signals, in: International Conference on Acoustics, Speech, and Signal Processing, 2011, pp. 3684–3687. Sprager, Zazula (bib17) 2009; 5 10.1016/j.patcog.2013.06.028_bib30 10.1016/j.patcog.2013.06.028_bib28 10.1016/j.patcog.2013.06.028_bib29 Snedecor (10.1016/j.patcog.2013.06.028_bib38) 1967 Gafurov (10.1016/j.patcog.2013.06.028_bib10) 2006 10.1016/j.patcog.2013.06.028_bib20 10.1016/j.patcog.2013.06.028_bib21 10.1016/j.patcog.2013.06.028_bib22 10.1016/j.patcog.2013.06.028_bib24 10.1016/j.patcog.2013.06.028_bib25 Kittler (10.1016/j.patcog.2013.06.028_bib35) 1998; 20 10.1016/j.patcog.2013.06.028_bib26 10.1016/j.patcog.2013.06.028_bib27 Gafurov (10.1016/j.patcog.2013.06.028_bib11) 2009; 2009 Yang (10.1016/j.patcog.2013.06.028_bib1) 2008; 29 Trivino (10.1016/j.patcog.2013.06.028_bib18) 2010; 43 Gafurov (10.1016/j.patcog.2013.06.028_bib23) 2007; 2 Lipkus (10.1016/j.patcog.2013.06.028_bib36) 2006; 26 10.1016/j.patcog.2013.06.028_bib8 10.1016/j.patcog.2013.06.028_bib9 10.1016/j.patcog.2013.06.028_bib6 10.1016/j.patcog.2013.06.028_bib7 10.1016/j.patcog.2013.06.028_bib5 Alvarez-Alvarez (10.1016/j.patcog.2013.06.028_bib19) 2012; 20 10.1016/j.patcog.2013.06.028_bib3 10.1016/j.patcog.2013.06.028_bib31 10.1016/j.patcog.2013.06.028_bib32 10.1016/j.patcog.2013.06.028_bib33 Altun (10.1016/j.patcog.2013.06.028_bib2) 2010; 43 10.1016/j.patcog.2013.06.028_bib12 10.1016/j.patcog.2013.06.028_bib34 10.1016/j.patcog.2013.06.028_bib13 10.1016/j.patcog.2013.06.028_bib14 Sprager (10.1016/j.patcog.2013.06.028_bib17) 2009; 5 10.1016/j.patcog.2013.06.028_bib15 10.1016/j.patcog.2013.06.028_bib37 Cook (10.1016/j.patcog.2013.06.028_bib4) 2004 10.1016/j.patcog.2013.06.028_bib16
References_xml	– reference: E. Vildjiounaite, S.-M. Makela, M. Lindholm, R. Riihimaki, V. Kyllonen, J. Mantyjarvi, H. Ailisto, Unobtrusive multimodal biometrics for ensuring privacy and information security with personal devices, in: 4th International Conference on Pervasive Computing, PERVASIVE, 2006, pp. 187–201. – reference: D. Gafurov, P. Bours, Improved hip based individual recognition using wearable motion recording sensor, in: Security Technology, Disaster Recovery and Business Continuity, vol. 122, Communications in Computer and Information Science, Springer, Berlin, Heidelberg, 2010, pp. 179–186. – reference: D. Gafurov, Performance and Security Analysis, Ph.D. Thesis, Faculty of Mathematics and Natural Sciences at the University of Oslo, 2008. – reference: D. Gafurov, E. Snekkenes, P. Bours, Gait authentication and identification using wearable accelerometer sensor, in: 5th IEEE Workshop on Automatic Identification Advanced Technologies, 2007, pp. 220–225. – volume: 2 start-page: 491 year: 2007 end-page: 502 ident: bib23 article-title: Spoof attacks on gait authentication system publication-title: IEEE Transactions on Information Forensics and Security – reference: C. Nickel, H. Brandt, C. Busch, Classification of acceleration data for biometric gait recognition on mobile devices, in: BIOSIG, 2011, pp. 57–66. – reference: J. Mantyjarvi, M. Lindholm, E. Vildjiounaite, S.-M. Makela, H. Ailisto, Identifying users of portable devices from gait pattern with accelerometers, in: Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 2, 2005, pp. 973–976. – reference: Kionic Inc., KXTF9, – year: 1967 ident: bib38 article-title: Statistical Methods – reference: A. Kale, N. Cuntoor, B. Yegnanarayana, A. Rajagopalan, R. Chellappa, Gait analysis for human identification, in: Audio– and Video–Based Biometric Person Authentication LNCS, 2003, pp. 706–714. – start-page: 51 year: 2006 end-page: 59 ident: bib10 article-title: Biometric gait authentication using accelerometer sensor publication-title: Journal of Computers – volume: 29 start-page: 2213 year: 2008 end-page: 2220 ident: bib1 article-title: Using acceleration measurements for activity recognition publication-title: Pattern Recognition Letters – volume: 43 start-page: 2572 year: 2010 end-page: 2581 ident: bib18 article-title: Application of the computational theory of perceptions to human gait pattern recognition publication-title: Pattern Recognition – volume: 20 start-page: 205 year: 2012 end-page: 223 ident: bib19 article-title: Human gait modeling using a genetic fuzzy finite state machine publication-title: IEEE Transactions on Fuzzy Systems – year: 2004 ident: bib4 article-title: Smart Environments – reference: M.O. Derawi, P. Bours, K. Holien, Improved cycle detection for accelerometer based gait authentication, in: Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010, pp. 312–317. – reference: L. Rong, Z. Jianzhong, L. Ming, H. Xiangfeng, A wearable acceleration sensor system for gait recognition, in: 2nd IEEE Conference on Industrial Electronics and Applications, 2007, pp. 2654–2659. – reference: P. Phillips, D. Blackburn, M. Bone, P. Grother, R. Micheals, E. Tabassi, Face recognition vendor test, – reference: D. Gafurov, E. Snekkenes, P. Bours, Improved gait recognition performance using cycle matching, in: 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops (WAINA), 2010, pp. 836–841. – reference: H.J. Ailisto, M. Lindholm, J. Mantyjarvi, E. Vildjiounaite, S. Makela, Identifying people from gait pattern with accelerometers, in: Biometric Technology for Human Identification, SPIE, vol. 5779, 2005, pp. 7–14. – reference: Y. Makihara, N.T. Trung, H. Nagahara, R. Sagawa, Y. Mukaigawa, Y. Yagi, Phase registration of a single quasi-periodic signal using self dynamic time warping, in: The Tenth Asian Conference on Computer Vision, Springer-Verlag, 2010, pp. 667–678. – reference: T. Kobayashi, K. Hasida, N. Otsu, Rotation invariant feature extraction from 3-D acceleration signals, in: International Conference on Acoustics, Speech, and Signal Processing, 2011, pp. 3684–3687. – reference: N. Trung, Y. Makihara, H. Nagahara, Y. Mukaigawa, Y. Yagi, Performance evaluation of gait recognition using the largest inertial sensor-based gait database, in: Proceedings of the 5th IAPR International Conference on Biometrics, 2012, pp. 360–366. – reference: N. Trung, Y. Makihara, H. Nagahara, R. Sagawa, Y. Mukaigawa, Y. Yagi, Phase registration in a gallery improving gait authentication, in: International Joint Conference on Biometrics (IJCB2011), IEEE and IAPR, 2011, pp. 1–7. – reference: ZMP Inc., IMUZ, – reference: J.C. Augusto, C.D. Nugent, A new architecture for smart homes based on ADB and temporal reasoning, in: Toward a Human Friendly Assistive Environment, Proceedings of 2nd International Conference On Smart homes and health Telematic, ICOST2004, 2004, pp. 106–113. – reference: J.R. Kwapisz, G.M. Weiss, S.A. Moore, Cell phone based biometric identification, in: IEEE Fourth International Conference on Biometrics: Theory, Applications and Systems, 2010, pp. 1–7. – volume: 5 start-page: 369 year: 2009 end-page: 378 ident: bib17 article-title: A cumulant-based method for gait identification using accelerometer data with principal component analysis and support vector machine publication-title: WSEAS Transactions on Signal Processing – reference: , In Japanese. – reference: D. Gafurov, Security analysis of impostor attempts with respect to gender in gait biometrics, in: First IEEE International Conference on Biometrics: Theory, Applications, and Systems, 2007, pp. 1–6. – reference: M.O. Derawi, C. Nickely, P. Bours, C. Busch, Unobtrusive user-authentication on mobile phones using biometric gait recognition, in: 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010, pp. 306–311. – reference: . – reference: , 2002. – reference: B. Huang, M. Chen, P. Huang, Y. Xu, Gait modeling for human identification, in: IEEE International Conference on Robotics and Automation, 2007, pp. 4833–4838. – reference: S. Bonnet, P. Jallon, Hidden markov models applied onto gait classification, in: 18th European Signal Processing Conference (EUSIPCO-2010), 2010, pp. 929–933. – reference: L. Rong, D. Zhiguo, Z. Jianzhong, L. Ming, Identification of individual walking patterns using gait acceleration, in: The 1st International Conference on Bioinformatics and Biomedical Engineering, 2007, pp. 543–546. – volume: 26 start-page: 263 year: 2006 end-page: 265 ident: bib36 article-title: A proof of the triangle inequality for the Tanimoto distance publication-title: Journal of Mathematical Chemistry – volume: 43 start-page: 3605 year: 2010 end-page: 3620 ident: bib2 article-title: Comparative study on classifying human activities with miniature inertial and magnetic sensors publication-title: Pattern Recognition – reference: F. Juefei-Xu, C. Bhagavatula, A. Jaech, U. Prasad, M. Savvides, Gait-id on the move: pace independent human identification using cell phone accelerometer dynamics, in: IEEE 5th International Conference on Biometrics, 2012, pp. 8–15. – volume: 2009 start-page: 1 year: 2009 end-page: 16 ident: bib11 article-title: Gait recognition using wearable motion recording sensors publication-title: EURASIP Journal on Advances in Signal Processing – volume: 20 start-page: 226 year: 1998 end-page: 239 ident: bib35 article-title: On combining classifiers publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence – year: 2004 ident: 10.1016/j.patcog.2013.06.028_bib4 – ident: 10.1016/j.patcog.2013.06.028_bib25 doi: 10.1007/978-3-642-17610-4_20 – ident: 10.1016/j.patcog.2013.06.028_bib7 doi: 10.1109/ICASSP.2011.5947150 – ident: 10.1016/j.patcog.2013.06.028_bib28 – ident: 10.1016/j.patcog.2013.06.028_bib3 – volume: 20 start-page: 226 issue: 3 year: 1998 ident: 10.1016/j.patcog.2013.06.028_bib35 article-title: On combining classifiers publication-title: IEEE Transactions on Pattern Analysis and Machine Intelligence doi: 10.1109/34.667881 – ident: 10.1016/j.patcog.2013.06.028_bib30 doi: 10.1109/BTAS.2012.6374552 – ident: 10.1016/j.patcog.2013.06.028_bib5 doi: 10.1117/12.603331 – volume: 43 start-page: 3605 issue: 10 year: 2010 ident: 10.1016/j.patcog.2013.06.028_bib2 article-title: Comparative study on classifying human activities with miniature inertial and magnetic sensors publication-title: Pattern Recognition doi: 10.1016/j.patcog.2010.04.019 – ident: 10.1016/j.patcog.2013.06.028_bib32 – ident: 10.1016/j.patcog.2013.06.028_bib9 doi: 10.1007/3-540-44887-X_82 – ident: 10.1016/j.patcog.2013.06.028_bib14 doi: 10.1109/ICBBE.2007.142 – volume: 5 start-page: 369 issue: 11 year: 2009 ident: 10.1016/j.patcog.2013.06.028_bib17 article-title: A cumulant-based method for gait identification using accelerometer data with principal component analysis and support vector machine publication-title: WSEAS Transactions on Signal Processing – volume: 20 start-page: 205 issue: 2 year: 2012 ident: 10.1016/j.patcog.2013.06.028_bib19 article-title: Human gait modeling using a genetic fuzzy finite state machine publication-title: IEEE Transactions on Fuzzy Systems doi: 10.1109/TFUZZ.2011.2171973 – ident: 10.1016/j.patcog.2013.06.028_bib22 doi: 10.1109/AUTOID.2007.380623 – ident: 10.1016/j.patcog.2013.06.028_bib15 doi: 10.1109/IIHMSP.2010.84 – ident: 10.1016/j.patcog.2013.06.028_bib24 doi: 10.1109/BTAS.2007.4401905 – volume: 26 start-page: 263 year: 2006 ident: 10.1016/j.patcog.2013.06.028_bib36 article-title: A proof of the triangle inequality for the Tanimoto distance publication-title: Journal of Mathematical Chemistry doi: 10.1023/A:1019154432472 – volume: 2009 start-page: 1 year: 2009 ident: 10.1016/j.patcog.2013.06.028_bib11 article-title: Gait recognition using wearable motion recording sensors publication-title: EURASIP Journal on Advances in Signal Processing doi: 10.1155/2009/415817 – ident: 10.1016/j.patcog.2013.06.028_bib20 doi: 10.1109/ICB.2012.6199833 – ident: 10.1016/j.patcog.2013.06.028_bib21 doi: 10.1007/11748625_12 – ident: 10.1016/j.patcog.2013.06.028_bib12 doi: 10.1109/WAINA.2010.145 – ident: 10.1016/j.patcog.2013.06.028_bib16 doi: 10.1109/IJCB.2011.6117527 – ident: 10.1016/j.patcog.2013.06.028_bib6 doi: 10.1109/ICASSP.2005.1415569 – volume: 29 start-page: 2213 issue: 16 year: 2008 ident: 10.1016/j.patcog.2013.06.028_bib1 article-title: Using acceleration measurements for activity recognition publication-title: Pattern Recognition Letters doi: 10.1016/j.patrec.2008.08.002 – ident: 10.1016/j.patcog.2013.06.028_bib29 – ident: 10.1016/j.patcog.2013.06.028_bib34 doi: 10.1007/978-3-642-19318-7_52 – ident: 10.1016/j.patcog.2013.06.028_bib27 doi: 10.1109/IIHMSP.2010.83 – ident: 10.1016/j.patcog.2013.06.028_bib13 doi: 10.1109/ICIEA.2007.4318894 – ident: 10.1016/j.patcog.2013.06.028_bib33 – volume: 43 start-page: 2572 issue: 7 year: 2010 ident: 10.1016/j.patcog.2013.06.028_bib18 article-title: Application of the computational theory of perceptions to human gait pattern recognition publication-title: Pattern Recognition doi: 10.1016/j.patcog.2010.01.017 – ident: 10.1016/j.patcog.2013.06.028_bib31 – ident: 10.1016/j.patcog.2013.06.028_bib8 doi: 10.1109/BTAS.2010.5634532 – volume: 2 start-page: 491 issue: 3 year: 2007 ident: 10.1016/j.patcog.2013.06.028_bib23 article-title: Spoof attacks on gait authentication system publication-title: IEEE Transactions on Information Forensics and Security doi: 10.1109/TIFS.2007.902030 – ident: 10.1016/j.patcog.2013.06.028_bib37 – year: 1967 ident: 10.1016/j.patcog.2013.06.028_bib38 – start-page: 51 year: 2006 ident: 10.1016/j.patcog.2013.06.028_bib10 article-title: Biometric gait authentication using accelerometer sensor publication-title: Journal of Computers – ident: 10.1016/j.patcog.2013.06.028_bib26 doi: 10.1109/ROBOT.2007.364224
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Snippet	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...
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SubjectTerms	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
Title	The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication
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