Research on Accurate Gesture Recognition Algorithm in Complex Environment Based on Machine Vision

Authors

Xu Sheng, 1. School of Electronic and Information Engineering, Nantong Vocational University, Nantong 226007, China; ;2. The East China Science and Technology Research Institute of Changshu Co., Ltd, Changshu 215500, China; ;
Wenyu Feng, 3. School of Electrical Engineering/School of Zhangjian, Nantong University, Nantong 226007 China; ;
Zhicheng Liu, 3. School of Electrical Engineering/School of Zhangjian, Nantong University, Nantong 226007 China; ;
Xintao Tu, 3. School of Electrical Engineering/School of Zhangjian, Nantong University, Nantong 226007 China; ;
Minrui Fei, 4. School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 310053, China; ;
Kun Zhang, 3. School of Electrical Engineering/School of Zhangjian, Nantong University, Nantong 226007 China; ;5. Nantong Key Laboratory of Intelligent Control and Intelligent Computing, Nantong 226007, China;

Abstract

Abstract: To address the issue of cross infection caused by elevator public buttons during COVID-19, a software algorithm based on machine vision for non-contact control of public buttons by gesture recognition is designed. In order to improve the accuracy of gesture recognition, an improved YOLOv4 algorithm is proposed. A Ghost module is designed based on attention mechanism, and the ResBlock module in YOLOv4 is improved to Ghost module. The experimental results show that, in the task of gesture recognition, the detection speed is improved by 14% and the detection accuracy is improved by 0.1% compared with the original model. The improved YOLOv4 algorithm is applied to the non-contact elevator buttons control system based on vision. The experimental results show that the detection accuracy reaches 98%, which meets the requirements of non-contact control for public elevators.

Recommended Citation

Sheng, Xu; Feng, Wenyu; Liu, Zhicheng; Tu, Xintao; Fei, Minrui; and Zhang, Kun (2021) "Research on Accurate Gesture Recognition Algorithm in Complex Environment Based on Machine Vision," Journal of System Simulation: Vol. 33: Iss. 10, Article 19.
DOI: 10.16182/j.issn1004731x.joss.21-FZ0668
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss10/19

First Page

2460

Revised Date

2021-08-18

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-FZ0668

Last Page

2469

CLC

TP391

Recommended Citation

Xu Sheng, Feng Wenyu, Liu Zhicheng, Tu Xintao, Fei Minrui, Zhang Kun. Research on Accurate Gesture Recognition Algorithm in Complex Environment Based on Machine Vision[J]. Journal of System Simulation, 2021, 33(10): 2460-2469.

Corresponding Author

Kun Zhang,

DOI

10.16182/j.issn1004731x.joss.21-FZ0668