Life detection and non-contact respiratory rate measurement in cluttered environments
| Autor: | Shuai Zhang, Shiqi Li, Haipeng Wang, Shuze Wang |
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| Rok vydání: | 2020 |
| Předmět: |
Pixel
Spatial filter Computer Networks and Communications Computer science business.industry Frame (networking) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering 02 engineering and technology Convolutional neural network Compensation (engineering) ComputingMethodologies_PATTERNRECOGNITION Histogram of oriented gradients Hardware and Architecture Filter (video) 0202 electrical engineering electronic engineering information engineering Media Technology RGB color model Computer vision Artificial intelligence business Software |
| Zdroj: | Multimedia Tools and Applications. 79:32065-32077 |
| ISSN: | 1573-7721 1380-7501 |
| DOI: | 10.1007/s11042-020-09510-4 |
| Popis: | A method is proposed in this paper for life detection and non-contact respiratory rate measurement in cluttered environments. Only an RGB video of the detection area is required. In the method, spatial filtering is firstly applied to each frame of the video for image denoising. Gray level compensation follows to compensate for the change of gray level caused by the environment light. Thirdly, the gray levels of each pixel over time are filtered separately by a low-pass filter. At last, the human is located and the respiratory rate is measured. Tests on a self-made dataset show that an accuracy of 76.7% is achieved by the proposed method, which is better than that of the Convolutional Neural Networks (30%) and the histogram of oriented gradients (3.3%). |
| Databáze: | OpenAIRE |
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