Title
I-vector analysis for Gait-based Person Identification using smartphone inertial signals.
Abstract
This paper describes and evaluates an i-vector based approach for Gait-based Person Identification (GPI) using inertial signals from a smartphone. This approach includes two variability compensation strategies (Linear Discrimination Analysis (LDA) and Probabilistic LDA) for dealing with the gait variability due to different recording sessions or different activities carried out by the user. This study uses a public available dataset that includes recordings from 30 users performing three different activities: walking, walking-upstairs and walking-downstairs.
Year
DOI
Venue
2017
10.1016/j.pmcj.2016.09.007
Pervasive and Mobile Computing
Keywords
Field
DocType
I-vector analysis,PLDA compensation,Gait recognition,Person identification,Smartphone inertial signals
Inertial frame of reference,I vector,Compensation strategy,Gait,Computer science,Word error rate,Speech recognition,Gaussian,Probabilistic logic
Journal
Volume
ISSN
Citations 
38
1574-1192
1
PageRank 
References 
Authors
0.37
30
5