TY  - JOUR
PY  - 2023//
TI  - A computer vision monitoring for human fall using visible light camera and thermal imager
JO  - International Journal of Modelling, Identification and Control
A1  - Yuan, Baolong
A1  - Wang, Yanhui
A1  - Wang, Xin
SP  - 145
EP  - 153
VL  - 43
IS  - 2
N2  - In order to solve the problems of image blur, uneven illumination and object occlusion in visual monitoring, a human fall detection algorithm based on visible light camera and thermal imager is proposed in this paper. Firstly, the visible light and thermal images are denoised to reduce the interference of noise. Secondly, the skeleton and joint coordinates of the human body are extracted through the lightweight human posture recognition model. Finally, three human posture parameters are designed as recognition features to achieve accurate fall recognition. The method is verified on self-built datasets and public datasets. The experimental results show that the accuracy of the method is 0.93 and 0.94 respectively. Compared with the most advanced algorithms, the proposed method has higher accuracy and better real-time performance.<p />  <p>Language: en</p>
LA  - en
SN  - 1746-6172
UR  - http://dx.doi.org/10.1504/IJMIC.2023.132608
ID  - ref1
ER  -