Intelligent invigilator system based on target detection.
Multimed Tools Appl
; : 1-23, 2023 Apr 29.
Article
in English
| MEDLINE | ID: covidwho-2320577
ABSTRACT
Affected by the COVID-19 epidemic, the final examinations at many universities and the recruitment interviews of enterprises were forced to be transferred to online remote video invigilation, which undoubtedly improves the space and possibility of cheating. To solve these problems, this paper proposes an intelligent invigilation system based on the EfficientDet target detection network model combined with a centroid tracking algorithm. Experiments show that cheating behavior detection model proposed in this paper has good detection, tracking and recognition effects in remote testing scenarios. Taking the EfficientDet network as the detection target, the average detection accuracy of the network is 81%. Experiments with real online test videos show that the cheating behavior detection accuracy can reach 83.1%. In addition, to compensate for the shortage of image detection, we also design an audio detection module to carry out auxiliary detection and forensics. The audio detection module is used to continuously detect the environmental sound of the examination room, save suspicious sounds and provide evidence for judging cheating behavior.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Diagnostic study
Language:
English
Journal:
Multimed Tools Appl
Year:
2023
Document Type:
Article
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