발간년도 : [2021]
| 논문정보 |
|
| 논문명(한글) |
[Vol.16, No.5] Cheating Detection System Through Eye Position Tracking |
|
| 논문투고자 |
Sung-Hun Choi, Sang-Joon Hong, Shin-Woong Kim, Ik-Su Kim |
|
| 논문내용 |
COVID-19 is prevalent around the world. Since COVID-19 is very dangerous to humans, many institutions are conducting online exam. However, online exams have the problem of cheating. In the CBT program, each examinee is given a different order of papers. However, since the order of the problems is different, it causes a disadvantageous situation for the examinee who is assigned to the problem with high difficulty for the first time. Also, this method does not prevent cheating performed alone. Company M's program prevents cheating by monitoring examinees with cameras mounted on mobile phones and computers. However, in this method, the examinee can commit cheating using the blind spots of the cameras. In this paper, we propose a cheating detection system using facial recognition technology to improve the problems of the existing cheating detection system. The proposed system consists of an examinee mode and an administrator mode. In the examinee mode, when the test starts, if an examinee places his or her face in a rectangular area on the screen and leaves the area for more than 2 seconds, it is considered cheating. In the administrator mode, the administrator can check the video of all examinees and whether there is any cheating in real time. |
|
| 첨부논문 |
|
|
|
|
|
자료실 > 논문지 
