Deakin home > Deakin University Library > Deakin Research Online > Driver recognition based on dynamic handgrip pattern on steeling wheel

Driver recognition based on dynamic handgrip pattern on steeling wheel

Chen, Ronghua, She, Mary Fenghua, Wu, Yuchuan, Sun, Xiangping and Kong, Lingxue 2011, Driver recognition based on dynamic handgrip pattern on steeling wheel, in SNPD 2011 : Proceedings of the 12th ACIS International Conference on Software Engineering, Artificial Intelligence Networking and Parallel Distributed Computing, IEEE, Piscataway, N. J., pp. 107-112.

Attached Files (Some files may be inaccessible until you login with your Deakin Research Online credentials)
Name Description MIMEType Size Downloads

Title Driver recognition based on dynamic handgrip pattern on steeling wheel
Author(s) Chen, Ronghua
She, Mary Fenghua
Wu, Yuchuan
Sun, Xiangping
Kong, Lingxue
Conference name ACIS International Conference on Software Engineering, Artificial Intelligence Networking and Parallel Distributed Computing (12th : 2011 : Sydney, N. S. W.)
Conference location Sydney, N. S. W.
Conference dates 6-8 July 2011
Title of proceedings SNPD 2011 : Proceedings of the 12th ACIS International Conference on Software Engineering, Artificial Intelligence Networking and Parallel Distributed Computing
Editor(s) [Unknown]
Publication date 2011
Conference series Software Engineering, Artificial Intelligence Networking and Parallel Distributed Computing International Conference
Start page 107
End page 112
Publisher IEEE
Place of publication Piscataway, N. J.
Keyword(s) driver verification
car security
haptic sensing
biometric authentication
grasping features
handgrip recognition
Summary This paper proposes a novel biometric authentication method based on the recognition of drivers' dynamic handgrip on steering wheel. A pressure sensitive mat mounted on a steering wheel is employed to collect handgrip data exerted by the hands of drivers who intend to start the vehicle. Then, the likelihood-ratio-based classifier is designed to distinguish rightful driver of a car after analyzing their inherent dynamic features of grasping. The experimental results obtained in this study show that mean acceptance rates of 85.4% for the trained subjects and mean rejection rates of 82.65% for the un-trained ones are achieved by the classifier in the two batches of testing. It can be concluded that the driver verification approach based on dynamic handgrip recognition on steering wheel is a promising biometric technology and will be further explored in the near future in smart car design.
ISBN 9780769544755
9781457708961
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 861604 Integrated Systems
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2011, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30042246

Document type: Conference Paper
Collection: Centre for Material and Fibre Innovation
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in Deakin Research Online is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 49 Abstract Views, 5 File Downloads  -  Detailed Statistics
Created: Tue, 14 Feb 2012, 15:23:25 EST