Accurate region of interest selection for video based heart rate monitoring for a person driving a car
| Autor: | Loh Siu Hong, Hian Phin Yeoh, Teh Peh Chiong, Humaira Nisar, Lai Koon Chun |
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| Rok vydání: | 2017 |
| Předmět: |
Pixel
Channel (digital image) Computer science Facial motion capture business.industry 0206 medical engineering Fast Fourier transform ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology 020601 biomedical engineering Signal 03 medical and health sciences 0302 clinical medicine Motion artifacts Region of interest Discrete cosine transform RGB color model Computer vision Artificial intelligence business 030217 neurology & neurosurgery |
| Zdroj: | TENCON 2017 - 2017 IEEE Region 10 Conference. |
| DOI: | 10.1109/tencon.2017.8228318 |
| Popis: | In this paper, a video based heart rate monitoring system for a person driving a car has been proposed using the face of the driver as region of interest. Challenges such as illumination and motion artifacts are present when the car is moving in real life. We have proposed methods for tackling insufficient illumination and face tracking. The video for heart rate measurement is acquired at a rate of 30 fps with a resolution of 640×480 pixels for different illumination and car speeds. The video is recorded using dash cam. We apply insufficient and irregular illumination compensation algorithm in the preprocessing stage. The forehead is tracked by using black pixel tracking algorithm. The forehead is divided into many smaller blocks for correct region of interest selection based on heart rate measurements. The photoplethysmography (PPG) signal is extracted by separating the video frames into three RGB traces, and considering G channel only for further processing. Fast Fourier Transform is applied to the G channel traces, followed by band pass filtering. The peak frequency of the resultant signal determines the heart rate (converted to beats per minute (bpm)). The average error in the heart rate measurement for our proposed system is 2.734 bpm. |
| Databáze: | OpenAIRE |
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