China using facial recognition technology to name and shame jaywalkers
Offenders are photographed crossing on red lights in four cities and their details are later beamed onto public screens at junctions
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Chinese cities are cracking down on jaywalkers by installing facial recognition kits at intersections to identify and shame them by posting their photographs on public screens, state media reported.
It is the latest use of the technology in China where it has been used by fast-food chain KFC to predict orders and in public conveniences to foil toilet paper thefts.
Cities in four provinces are using the hardware to keep pedestrians from crossing at red lights, according to the state-run Xinhua news agency.
The technology has detected more than 6,000 cases of people crossing red lights since it was installed in early May in Jinan, the capital of eastern Shandong province.
The facial recognition equipment takes photographs and a 15-second video of jaywalkers, whose images instantly appear on a screen, showing them that they have been caught, Xinhua said.
The pictures are matched with images in a provincial police database.
“Within 20 minutes, the offender’s photograph and personal information such as their ID number and home address are displayed on the screen at the crossroad,” Xinhua said.
Traffic police give the offenders the choice between paying the equivalent of US$3 in a fine, taking a half-hour course on traffic rules or spending 20 minutes helping a traffic officer.
Jinan traffic police department may also publish the offender’s information on its social media account.
“Since the new technology has been adopted, the cases of jaywalking have been reduced from 200 to 20 each day at the major intersection of Jingshi and Shungeng roads,” Jinan police officer Li Yong was quoted as saying by Xinhua.
The report comes after a video appeared on social media earlier this month showing a woman get hit by a taxi on a crossing and then run over by a car. She later died.
The footage sparked outrage at the indifference of other pedestrians and drivers who did not stop to help her.
