Gait-ID on the move: Pace independent human identification using cell phone accelerometer dynamics

2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012

Volumn , Issue , 2012, Pages 8-15

  Juefei Xu, Felix ^a,b   Bhagavatula, Chandrasekhar ^a,b   Jaech, Aaron ^a   Prasad, Unni ^a,b   Savvides, Marios ^a,b  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELL PHONE; CONTINUOUS WAVELET TRANSFORM; CYCLOSTATIONARITY; FALSE ACCEPT RATE; GAIT RECOGNITION; HUMAN IDENTIFICATION; SPECTROGRAMS;

BIOMETRICS; GAIT ANALYSIS; MOBILE DEVICES;

MOBILE TELECOMMUNICATION SYSTEMS;

EID: 84871960939     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BTAS.2012.6374552     Document Type: Conference Paper

References (15)

1. Android Developers. API (public class:sensormanager). http://developer. android. com/reference/android/hardware/SensorManager.html. 2
2. W. Baarda. S-transformations and criterion matrices. Band 5 der Reihe 1. Netherlands Geodetic Commission, 1973. 5
3. H. Chan, H. Zheng, H. Wang, R. Gawley, M. Yang, and R. Sterritt. Feasibility study on iphone accelerometer for gait detection. In Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2011 5th International Conference on, pages 184-187, may 2011. 2
4. C.-C. Chang and C.-J. Lin. Libsvm: A library for support vector machines. ACM Trans. Intell. Syst. Technol., 2(3):27:1-27:27, May 2011. 6
5. D. Gafurov, E. Snekkenes, and P. Bours. Gait authentication and identification using wearable accelerometer sensor. In Automatic Identification Advanced Technologies, 2007 IEEE Workshop on, pages 220-225, june 2007. 1, 2
6. J. Han and B. Bhanu. Individual recognition using gait energy image. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 28(2):316-322, feb. 2006. 1
7. J. R. Kwapisz, G. M. Weiss, and S. A. Moore. Cell phone-based biometric identification. In Biometrics: Theory Applications and Systems (BTAS), 2010 Fourth IEEE International Conference on, pages 1-7, sept. 2010. 2
8. W. C. Lang and K. Forinash. Time-frequency analysis with the continuous wavelet transform. American Journal of Physics, 66(9):794, Sept. 1998. 4
9. N. Liu, J. Lu, and Y.-P. Tan. Joint subspace learning for view-invariant gait recognition. Signal Processing Letters, IEEE, 18(7):431-434, july 2011. 1
10. G. Pan, Y. Zhang, and Z. Wu. Accelerometer-based gait recognition via voting by signature points. Electronics Letters, 45(22):1116-1118, 22 2009. 1
11. L. Rong, Z. Jianzhong, L. Ming, and H. Xiangfeng. A wearable acceleration sensor system for gait recognition. In Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conf. on, pages 2654-2659, may 2007. 1, 2
12. W. Shi, J. Yang, Y. Jiang, F. Yang, and Y. Xiong. Senguard: Passive user identification on smartphones using multiple sensors. In Wireless and Mobile Computing, Networking and Communications (WiMob), 2011 IEEE 7th International Conference on, pages 141-148, oct. 2011. 2
13. S. Sprager and D. Zazula. Impact of different walking surfaces on gait identification based on higher-order statistics of accelerometer data. In Signal and Image Processing Applications (ICSIPA), 2011 IEEE International Conference on, pages 360-365, nov. 2011. 2
14. D. Tao, X. Li, X. Wu, and S. Maybank. General tensor discriminant analysis and gabor features for gait recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 29(10):1700-1715, oct. 2007. 1
15. J. Zhang, J. Pu, C. Chen, and R. Fleischer. Low-resolution gait recognition. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 40(4):986-996, aug. 2010. 1