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Proceedings Paper

User discrimination in automotive systems
Author(s): Andrey Makrushin; Jana Dittmann; Claus Vielhauer; Marcus Leich
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Paper Abstract

The recently developed dual-view touch screens, which are announced to be installed in cars in a near future, give rise to completely new challenges in human-machine interaction. The automotive system should be able to identify if the driver or the passenger is currently interacting with the touch screen to provide a correct response to the touch. The optical devices, due to availability, acceptance by the users and multifunctional usage, approved to be the most appropriate sensing technology for driver/passenger discrimination. In this work the prototypic optical user discrimination system is implemented in the car simulator and evaluated in the laboratory environment with entirely controlled illumination. Three tests were done for this research. One of them examined if the near-infrared illumination should be switched on around the clock, the second one if there is a difference in discrimination performance between day, twilight and night conditions, and the third one examined how the intensive directional lighting influences the performance of the implemented user discrimination algorithm. Despite the high error rates, the evaluation results show that very simple computer vision algorithms are able to solve complicated user discrimination task. The average error rate of 10.42% (daytime with near-infrared illumination) is a very promising result for optical systems.

Paper Details

Date Published: 3 February 2011
PDF: 9 pages
Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 78700J (3 February 2011); doi: 10.1117/12.872453
Show Author Affiliations
Andrey Makrushin, Otto-von-Guericke-Univ. Magdeburg (Germany)
Jana Dittmann, Otto-von-Guericke-Univ. Magdeburg (Germany)
Claus Vielhauer, Otto-von-Guericke-Univ. Magdeburg (Germany)
Univ. of Applied Sciences Brandenburg (Germany)
Marcus Leich, Otto-von-Guericke-Univ. Magdeburg (Germany)

Published in SPIE Proceedings Vol. 7870:
Image Processing: Algorithms and Systems IX
Jaakko T. Astola; Karen O. Egiazarian, Editor(s)

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