Tokyo Olympics in 2020 to Identify athletes using facial recognition software

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Individuals in the Tokyo 2020 Olympics will be among 300,000 participants to be identified using facial acknowledgment innovation, organisers stated.

The security system being rolled out throughout the occasion’s locations will use innovation offered by NEC Corporation, which likewise provides mugshot-matching software to police forces in the UK.

It will be utilized to prevent individuals from taking gain access to cards and utilizing them to gain access to limited locations – rather, attendees will need to show that their facial image matches the one shared by the card.

All 300,000 people accredited to go to the occasion – from professional athletes and authorities through to team member and media agents – will have their facial images registered in the comparison database.

Facial recognition works with an algorithm comparing a “probe image” recorded by means of CCTV or another source, to a database of “contrast images”.

Nevertheless, even the most sophisticated systems have actually struggled to make matches when the database of contrast images is huge.

Although the Olympics and Paralympics think the innovation will “improve overall comfort and benefit”, the database of 300,000 people is most likely to posture an enormous test to NEC’s system.

A driving concern behind the implementation of the system was the fears of long queues forming throughout the peak of summer in Tokyo. More than 120 people have actually died in a record heatwave this year.

There are worries that such temperature levels could cause much more harm within the slow-moving lines of a high-security event.

“This newest technology will enable rigorous identification of certified individuals compared with relying exclusively on the eyes of security personnel,” said Tsuyoshi Iwashita, the Games’ executive director of security.

It “likewise makes it possible for quick entry to locations which will be essential in the extreme heat of summer season”, he included.

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