A Mask Wear Detection Access Control System Based on Improved SSD and Jetson Nano
[1]Mao Xiaobo,Xu Xiangyang,Li Nan,et al.A Mask Wear Detection Access Control System Based on Improved SSD and Jetson Nano[J].Journal of Zhengzhou University (Engineering Science),2021,42(06):87-94.[doi:10.13705/j.issn.1671-6833.2021.06.002]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
42
Number of periods:
2021 06
Page number:
87-94
Column:
Public date:
2021-11-10
- Title:
- A Mask Wear Detection Access Control System Based on Improved SSD and Jetson Nano
- Keywords:
- mask wear detection; access control system; object detection algorithm SSD; Jetson Nano; MobileNet-V3
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2021.06.002
- Abstract:
- In order to reduce the chance of cross infection caused by people not wearing masks during the epidemic, a mask wearing detection access control system based on improved SSD and Jetson Nano is designed to quickly detect whether pedestrians at the entrance and exit wear masks and control the opening and closing of the gate. Firstly, 6 000 training pictures suitable for the system are extracted from the two data sets of MAFA and WIDER FACE, which are used as the training set and 2 000 as the test set; Secondly, the pixel level transformations such as random rue and saturation and geometric level transformations such as random expansion and random clipping are used to enhance the small targets in the data set, so as to add more samples to the data set and enhance the generalization ability of the detection network; Thirdly, the VGG feature extraction network of the original SSD is replaced by MobileNet-V3, which makes use of its speed advantage of depth-wise separable convolution, as well as the optimization strategies such as H-Swish activation function with less computation and lightweight attention mechanism (squeeze and excite) to accelerate the detection and improve the accuracy. Finally, the detection network is transplanted to Jetson Nano, an artificial intelligence edge computing device with limited computing power, equipped with high-definition display, design a foldable parallelogram baffle, and select appropriate peripheral equipment to form a multi-functional access control system with epidemic prevention value to quickly detect whether pedestrians at the entrance and exit of public places wear masks. The test results on the embedded device are as follows: the target detection algorithm SSD with MobileNet-V3 as the feature extraction network obtains 78% MAP and FPS is 12. Compared with the original SSD algorithm with VGG as the feature extraction network (FPS is 2), the detection speed is increased five times. Facts have proved that the system not only ensures the real-time performance, but also takes into account the detection accuracy, so achieves the balance of accuracy and speed.
- References:
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Last Update:
2021-12-17