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Title: Driver tracking and posture detection using low-resolution infrared sensing
Authors: Amin, I.J.
Taylor, Andrew J.
Parkin, Robert M.
Keywords: Infrared sensing
Artificial Neural Network (ANN)
Machine vision
Intelligent safety system
Issue Date: 2007
Publisher: Professional Engineering Publishing / © IMECHE
Citation: AMIN, I.J., TAYLOR, A.J. and PARKIN, R.M., 2007. Driver tracking and posture detection using low-resolution infrared sensing. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 221(9), pp. 1079-1088.
Abstract: Intelligent sensors are playing an ever-increasing role in automotive safety. This paper describes the development of a low-resolution infrared (IR) imaging system for continuous tracking and identification of driver postures and movements. The resolution of the imager is unusually low at 16 x 16 pixels. An image processing technique has been developed using neural networks operating on a segmented thermographic image to categorize driver postures. The system is able reliably to identify 18 different driver positions, and results have been verified experimentally with 20 subjects driving in a car simulator. IR imaging offers several advantages over visual sensors; it will operate in any lighting conditions and is less intrusive in terms of the privacy of the occupants. Hardware costs for the low-resolution sensor are an order of magnitude lower than those of conventional IR imaging systems. The system has been shown to have the potential to play a significant role in future intelligent safety systems.
Description: This is an article from the journal, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering [© IMechE ]. It is also available at: http://dx.doi.org/10.1243/09544070JAUTO517
Version: Published
DOI: 10.1243/09544070JAUTO517
URI: https://dspace.lboro.ac.uk/2134/4712
ISSN: 0954-4070
Appears in Collections:Published Articles (Mechanical and Manufacturing Engineering)

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