A new mobile-payment system drawn up by Microsoft Research would identify customers participating in the Zero-Effort Payment service using unique identifiers in their smartphone’s Bluetooth stack when they enter a merchant’s store. Cameras and a Kinect sensor with facial-recognition technology deployed on site then would identify customers as they’re waiting to pay.
The system presents cashiers’ point-of-sale tablets with a choice of four facial images, and the system processes the transaction using preregistered payment credentials once the clerk picks the right image. The system sends a transaction confirmation to the customer via email, plus a 10-second video should they decide to contest the transaction.
WMPoweruser, which dubs itself as the largest independent Windows phone community, says Microsoft has been testing the service in its own cafeterias.
From a Microsoft Research report abstract about the service:
Device detection makes face recognition feasible by limiting the number of potential customers, while face recognition provides directional information that device detection lacks. Together, these technologies provide an ordering of likely candidates to a store employee, who makes the final determination of identity.
The service represents an attempt to provide a truly seamless mobile-payment experience, where users do not have to activate and sign in to a mobile app for the store’s proximity system to identify them, a process that likely dooms the long-term interest in using such an app. In fact, customers don’t have to do anything, except have their phone’s Bluetooth service activated. And many consumers have their phone’s Bluetooth already activated if they have Bluetooth-enabled vehicles so their phones are usable hands-free for calls.
Such a system would have to address the fact that consumers’ images are captured, and some customers might not want such “Big Brother” identification. But with cameras increasingly on almost every street corner and in almost every merchant location already, not always with the customer’s knowledge, the camera and image-capture issue might create only minimal push-back with some real-world education. But any broadly acknowledged misuse of the facial-recognition technology, by stores or government, quickly could doom any mobile-app services that relies on the imaging technology.
