Real-time fall detection system based on deep learning and infrared array sensors

In this paper, a novel fall detection algorithm based infrared image is proposed. Firstly, the RetinexNet algorithm is adopted for the infrared image pre-processing and enhancement, then the YOLOv3 algorithm is improved by adding three bounding boxes to achieve the task of falling posture detection and recognition, finally a fall data set collected by ourselves is utilized to train and test the algorithm. The experimental results shows that our proposed algorithm achieves excellent fall detection accuracy result and outperforms the traditional YOLOv3 algorithm, the average accuracy of our proposed algorithm is more than 90.86%, which meets the requirements of the fall detection task quite well.