Authors:
Maria De Marsico
;
Eduard Gabriel Fartade
and
Alessio Mecca
Affiliation:
Sapienza University of Rome, Italy
Keyword(s):
Biometric Authentication, Gait Recognition, Automatic Feature Extraction.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Biometrics
;
Biometrics and Pattern Recognition
;
Feature Selection and Extraction
;
Multimedia
;
Multimedia Signal Processing
;
Pattern Recognition
;
Telecommunications
;
Theory and Methods
Abstract:
Gait recognition has been traditionally tackled by computer vision techniques. As a matter of fact, this is a still
very active research field. More recently, the spreading use of smart mobile devices with embedded sensors
has also spurred the interest of the research community for alternative methods based on the gait dynamics
captured by those sensors. In particular, signals from the accelerometer seem to be the most suited for recognizing
the identity of the subject carrying the mobile device. Different approaches have been investigated
to achieve a sufficient recognition ability. This paper proposes an automatic extraction of the most relevant
features computed from the three raw accelerometer signals (one for each axis). It also presents the results
of comparing this approach with a plain Dynamic Time Warping (DTW) matching. The latter is computationally
more demanding, and this is to take into account when considering the resources of a mobile device.
Moreover, though being a k
ind of basic approach, it is still used in literature due to the possibility to easily
implement it even directly on mobile platforms, which are the new frontier of biometric recognition.
(More)