Orientation independent cell phone based gait authentication

12th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2014

Volumn , Issue , 2014, Pages 161-164

  Muaaz, Muhammad ^a   Mayrhofer, René ^b  

^a UNIVERSITY OF APPLIED SCIENCES UPPER AUSTRIA   (Austria)

^b JOHANNES KEPLER UNIVERSITY LINZ   (Austria)

Author keywords

Accelerometer; Gait recognition; Segmentation; Variance; Wavelets

Indexed keywords

ACCELEROMETERS; AUTHENTICATION; CELLULAR TELEPHONES; GAIT ANALYSIS; IMAGE SEGMENTATION; MOBILE COMPUTING; WALKING AIDS;

ACCELEROMETER SENSOR; GAIT RECOGNITION; MAGNITUDE DATA; NOISE ELIMINATION; REALISTIC SCENARIO; SENSOR ORIENTATION; VARIANCE; WAVELETS;

PATTERN RECOGNITION;

EID: 84942548975     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2684103.2684152     Document Type: Conference Paper

References (10)

1. H. Ailisto, M. Lindholm, J. Mantyjarvi, E. Vildjiounaite, and S. Makela. Identifying people from gait pattern with accelerometers. Number 7-14 in Biometric Technology for Human Identification II Bd. 5779, SPIE, 2005.
2. M. O. Derawi. Smartphones and Biometrics: Gait and Activity Recognition. PhD thesis, Gj0vik University College, November 2012.
3. J. Frank, S. Mannor, and D. Precup. Activity and gait recognition with time-delay embeddings. In AAAI, 2010.
4. D. Gafurov. Performance and Security Analysis of Gait-based User Authentication. PhD thesis, Universitas Osloensis, 2004.
5. 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. IEEE, 2010.
6. M. Muaaz and R. Mayrhofer. An analysis of different approaches to gait recognition using cell phone based accelerometers. In Proceedings of International Conference on Advances in Mobile Computing and Multimedia, pages 293-300. ACM, 2013.
7. M. Muaaz and C. Nickel. Influence of different walking speeds and surfaces on accelerometer-based biometric gait recognition. In Telecommunications and Signal Processing (TSP), 2012 35th International Conference on, pages 508-512, 2012.
8. C. Nickel. Accelerometer-based Biometric Gait Recognition for Authentication on Smartphones. PhD thesis, TU Darmstadt, June 2012.
9. D. B. Percival and A. T. Walden. Wavelet methods for time series analysis, volume 4. Cambridge University Press, 2006.
10. M. Tamviruzzaman, S. I. Ahamed, C. S. Hasan, and C. O'brien. epet: When cellular phone learns to recognize its owner. In Proceedings ofthe 2Nd ACM Workshop on Assurable and Usable Security Configuration, SafeConfig, pages 13-18. ACM, 2009.