Driver tracking and posture detection using low-resolution infrared sensing

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 − 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.

Keywords

infrared sensing artificial Neural Network (ANN)machine vision intelligent safety system

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References

Dissanayake

J. J.

Factors influential in making an injury severity difference to older drivers involved in fixed object-passenger car crashes. Accid. Analysis and Prev., 2002, 34 (5), 609–618.

Carr

Jackson

T. W.

Madden

D. J.

Cohen

H. J.

The effect of age on driving skills. J. Am. Geriatrics Soc., 1992, 40 (6), 567–573.

Lundberg

Hakamies-Blomqvist

Almkvist

Johansson

Impairments of some cognitive functions are common in crash-involved older drivers. Accid. Analysis and Prev., 1998, 30 (3), 371–377.

Reuben

D. B.

Assessment of older drivers. Clinics in Geriatric Med., 1993, 9 (2), 449–459.

Smith

D. B. D.

Meshkati

Robertson

M. M.

The older driver and passenger. In Automotive ergonomics (Eds Peacock

Karwowski

), 1993, p. 461 (Taylor and Francis, London).

Andreoni

Santambrogio

G. C.

Rabuffetti

Pedotti

Method for the analysis of posture and interface pressure of car drivers. Appl. Ergonomics, 2002, 33 (6), 511–522.

Rakheja

Haru

Boileau

P. E.

Seated occupant apparent mass characteristics under automotive postures and vertical vibration. J. Sound Vibr., 2002, 253 (1), 57–75.

Burney

S. G.

Williams

T. W.

Jones

C. H.

Applications of thermal imaging, 1988 (Institute of Physics Publishing, Bristol).

10.

Holst

G. C.

Common sense approach to thermal imaging, 2000 (SPIE-International Society for Optical Engineers, Bellingham, WA).

11.

Kulkarni

A. D.

Artificial neural networks for image understanding, 1993 (John Wiley & Sons, Inc., New York).

12.

Al-Habaibeh

Parkin

R. M.

An autonomous low-cost infrared system for the on-line monitoring of manufacturing processes using novelty detection. Int. J. Advd Mfg Technol., 2003, 22 (3–4), 249–258.

13.

Amin

I. J.

Taylor

A. J.

Parkin

R. M.

In-cabin occupant tracking using a low-cost infrared system. In Proceedings of the IEEE Mechatronics and Robotics Conference, Aachen, Germany, 2004.

14.

Amin

I. J.

Sensor fusion of visual and infrared system for monitoring people. MSc Thesis, Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, 2003, p. 187.