A study on gait recognition using LPC cepstrum for mobile terminal

The use of mobile terminals has been expanding dramatically in recent years as they evolve from a means of dispatching and gathering information to a highly functional tool that supports personal lifestyles and behavior. A mobile terminal is likely to store various kinds of personal information such as a calendar and contact information as well as key data to carry out online transactions. Losing one's mobile terminal therefore creates the possibility that one's personal information may fall into the wrong hands and be used for malicious purposes. We therefore propose a method of personal authentication using sensor data in a mobile terminal. First, we applied the LPC cepstrum to this authentication and checked for validity. We also evaluated the effectiveness of gait authentication using several frames.

[1]  S. J. Campanella.  DIGITAL SPEECH PROCESSING METHODS , 1972 .

[2]  Kirsi Helkala,et al.  Gait recognition using acceleration from MEMS , 2006, First International Conference on Availability, Reliability and Security (ARES'06).

[3]  M. P. Murray.  Gait as a total pattern of movement. , 1967, American journal of physical medicine.

[4]  古井 貞煕,et al.  Digital speech processing, synthesis, and recognition , 1989 .

[5]  H. S. Nagendraswamy,et al.  Gait recognition: An approach based on interval valued features , 2013, 2013 International Conference on Computer Communication and Informatics.

[6]  Gary M. Weiss,et al.  Cell phone-based biometric identification , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[7]  Patrick Bours,et al.  Towards an automatic gait recognition system using activity recognition (wearable based) , 2011, 2011 Third International Workshop on Security and Communication Networks (IWSCN).

[8]  Murray Mp,et al.  Gait as a total pattern of movement. , 1967 .

[9]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..