2 research outputs found

    Driver tracking and posture detection using low-resolution infrared sensing

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    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

    Automated people-counting by using low-resolution infrared and visual cameras

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    Non-contact counting of people in a specified area has many applications for safety, security and commercial purposes. Visible sensors have inherent limitations for this task, being sensitive to variations in ambient lighting and colours in the scene. Infrared imaging can overcome many of these problems, but normally hardware costs are prohibitively expensive. A system for counting people in a scene using a combination of low cost, low-resolution visual and infrared cameras is presented in this paper. The aim of this research was to assess the potential accuracy and robustness of systems using low-resolution images. This approach results in considerable savings on hardware costs, enabling the development of systems which may be implemented in a wide range of applications. The results of 18 experiments show that the system can be accurate to within 3% over a wide range of lighting conditions
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