CONTINUOUS REAL-TIME VEHICLE DRIVER AUTHENTICATION USING CONVOLUTIONAL NEURAL NETWORK BASED FACE RECOGNITION | Ekberjan Derman, Alber Ali Salah

Ekberjan Derman1 and Albert Ali Salah2;3
1 CuteSafe Technology, Gebze, Kocaeli, Turkey
ekberjan.derman@cutesafe.com
2 Department of Computer Engineering, Bogazici University, Bebek, Istanbul, Turkey
3 Future Value Creation Research Center, Nagoya University, Nagoya, Japan
salah@boun.edu.tr

Abstract

Continuous driver authentication is useful in the prevention of car thefts, fraudulent switching of designated drivers, and driving beyond a designated amount of time for asingle driver. In this paper, we propose a deep neural network based approach for real time and continuous authentication of vehicle drivers. Features extracted from pre-trained neural network models are classified with support vector classifiers. In order to examine realistic conditions, we collect 130 in-car driving videos from 52 different subjects. We investigate the conditions under which current face recognition technology will allow commercialization of continuous driver authentication.

Contact Us