1A1-G01 Abnormal Behavior Detection System for Elderly People Based on Rotary Drive of Laser Range Scanner(Welfare Robotics and Mechatronics (1))

2014 ◽  
Vol 2014 (0) ◽  
pp. _1A1-G01_1-_1A1-G01_4
Author(s):  
Kazuhiro TAJIMA ◽  
Naohiro KAWANO ◽  
Daisuke NISHIMURA ◽  
Hirokazu SEKI
Keyword(s):  
Elderly People ◽  
Detection System ◽  
Abnormal Behavior ◽  
Laser Range ◽  
Behavior Detection ◽  
Laser Range Scanner ◽  
Abnormal Behavior Detection ◽  
Rotary Drive

scholarly journals Examination of Abnormal Behavior Detection Based on Improved YOLOv3

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 197
Author(s):  
Meng-ting Fang ◽  
Zhong-ju Chen ◽  
Krzysztof Przystupa ◽  
Tao Li ◽  
Michal Majka ◽  
...  
Keyword(s):  
Detection Method ◽  
Abnormal Behavior ◽  
Detection Accuracy ◽  
Average Precision ◽  
Research Results ◽  
Behavior Detection ◽  
Abnormal Behavior Detection ◽  
The Mean ◽  
Examination Room ◽  
Detection Speed

Examination is a way to select talents, and a perfect invigilation strategy can improve the fairness of the examination. To realize the automatic detection of abnormal behavior in the examination room, the method based on the improved YOLOv3 (The third version of the You Only Look Once algorithm) algorithm is proposed. The YOLOv3 algorithm is improved by using the K-Means algorithm, GIoUloss, focal loss, and Darknet32. In addition, the frame-alternate dual-thread method is used to optimize the detection process. The research results show that the improved YOLOv3 algorithm can improve both the detection accuracy and detection speed. The frame-alternate dual-thread method can greatly increase the detection speed. The mean Average Precision (mAP) of the improved YOLOv3 algorithm on the test set reached 88.53%, and the detection speed reached 42 Frames Per Second (FPS) in the frame-alternate dual-thread detection method. The research results provide a certain reference for automated invigilation.

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