Chinese school's facial recognition system targets distracted students
Surely at one point or another you've been caught daydreaming at school, but in future it might not be a teacher catching you first.
In China, the Hangzhou No. 11 Middle School is trialling a smart classroom behaviour management system which uses cameras and facial recognition to keep track of student performance.
SEE ALSO:Chinese police used facial recognition to catch a suspect in a crowd of 60,000The system is able to measure the expressions of students, including anger, annoyance, surprise, and of course, happiness.
According to Hangzhou Network, the system can provide an alert to the teacher when a student's inattentive behaviour reaches a certain value.
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"The system is advanced enough to capture the subtle facial expressions in class," a school official told Zhejiang Daily, as per a translation by What's On Weibo.
"This data system can be used to analyze the behavior of the entire class. And of course, this is a very efficient way to check class attendance."
Yep, at least there's no need to do roll call. The system can crosscheck with database of student face images to verify who's present, with the attendance result generated in less than a minute.
While seemingly targeted at students, the system can also be be used to measure a teacher's performance based on the reactions of students.
One student told the news outlet that the system has perhaps the desired effect when it comes to performance.
"It is a way to monitor us," he said. "We see the cameras whenever we are about to fall asleep in class. And we are going to stay more alert because of that. It encourages us to behave well."
Despite online criticism, the school's principal Ni Ziyuan told Hangzhou Network the system will be installed in all classes during the summer holidays.
"With the aid of this management system, it is equivalent to having one additional teaching assistant for teachers, which can improve the pertinence of education and the effect of classroom teaching," Ni said.
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TopicsArtificial IntelligenceFacial RecognitionPrivacy
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