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Move over humans, this startup is making facial recognition for pets

Megvii says it can identify individual dogs by scanning their noses

This article originally appeared on ABACUS
If you’re a dog lover, you probably don’t need convincing that your furry friend is like no other. But just how exactly can you tell two pups apart? AI startup Megvii says they have an answer.
The company, known better as a supplier of facial recognition surveillance software to the Chinese government, is now dabbling in biometric recognition for animals. But rather than scanning the whole face of a dog, it focuses solely on one feature: The nose.

(Abacus is a unit of the South China Morning Post, which is owned by Alibaba -- a backer of Megvii.)

The technology is based on the idea that dogs are discernable by their nose prints, similar to how smartphones or law enforcement agencies use fingerprints to identify humans. Unlike the more prevalent identification method of chip implants, Megvii says nose printing is cheaper and less invasive.
Kennel clubs around the world are already known to register nose prints to locate lost or stolen dogs. One primitive way to take a nose print is by coating the nose with ink and pressing it against white cardboard.

Megvii’s method, however, doesn’t require smearing your dog’s snout. Just point your phone’s camera at the nose and the system will be able to locate key identifying markers, creating a unique profile of your dog in the database.

That would seem to require high-resolution images of your dog’s nose. Still, the company says using this method, it can verify a dog’s identity against an existing record with 95% accuracy. It also says the system can be used to identify a dog with “high precision” by checking it against records from a larger database, although the company didn’t elaborate on the accuracy rate in that scenario.

The system requires multiple shots of the nose to create a profile. (Picture: Megvii)
The idea of using AI to identify dogs isn’t new. A smartphone app called Finding Rover uses facial recognition to help locate lost dogs. Based on a machine learning algorithm developed at the University of Utah, the app collects photos of missing dogs from pet owners. The images are then matched against a database of dogs found by shelters or other app users.
The app’s founder says more than 15,000 pets have been reunited with their owners so far.
Megvii says besides identifying lost pets, its technology can also be used by authorities to monitor “uncivilized dog keeping” -- a term used in China to describe behavior like walking a dog without a leash or failing to scoop up dog poop.
Pet ownership, once branded as bourgeois by the Communist Party, has enjoyed a revival in recent decades thanks to an increasingly wealthy middle class.
China’s urban areas are home to more than 91 million pet dogs and cats, according to a pet industry report last year. But as the number of pet owners soars, so do complaints from citizens. Pet owners have been criticized for not cleaning up after their dogs or letting them roam around unrestrained. That has prompted local governments to impose strict regulations, which has in turn triggered outcry from pet owners.
A man takes a selfie with a Maltese dog during the 2019 Shanghai World Dog Show. (Picture: Hector Retamal/AFP)

In any case, there seems to be no lack of pet owners willing to splurge on their four-legged friends. And there are plenty of businesses betting on China’s growing pet industry.

Lufax, an online finance platform backed by China’s largest insurer, Ping An, rolled out a health insurance plan for pets this year. Customers need to scan the face of their pets to enroll or file a claim.

Bad news for owners of exotic pets, though: The scheme is currently only available for dogs and cats.

For more insights into China tech, sign up for our tech newsletters, subscribe to our Inside China Tech podcast, and download the comprehensive 2019 China Internet Report. Also roam China Tech City, an award-winning interactive digital map at our sister site Abacus.

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