Patent filings suggest dual biometrics from Apple, mask-agnostic facial recognition from GBT
Apple and startup GBT Technologies have each filed for patents on biometric capabilities for mobile devices.
Apple files to extend patent for multiple native smartphone biometrics
The U.S. Patent & Trademark Office (USPTO) has published a continuation of Apple’s first patent describing both Touch ID fingerprint and Face ID biometrics, which adds in 33 new patent claims for potential implementation in 2021 and 2022 iPhones, Patently Apple reports.
The patent for ‘Implementation of biometric authentication’ indicates how TouchID can be used on button-less phones if Face ID fails, and a password if both biometrics fail. It is unclear whether or not Apple plans to implement such options in the future.
The patent refers to using the biometric authentication to complete a transfer, autofill fields in a form, or log in to the device. The latest patent in Apple’s multi-modal biometric patent family builds on more than 400 claims in the original patent, and 29 added in a patent granted to the company in December.
USPTO recently published Apple’s patent for an under-display optical fingerprint biometric sensor based on a narrow field-of-view collimator.
Patently Apple suggests that the move may be due to FaceID recognition difficulties resulting from mask-wearing.
In April, Apple filed a patent for new biometric authentication sensors on wearable devices, through which would be able to recognize user inputs like voiced commands or silent gestures.
GBT files patent for facial recognition on mobile devices
California-based GBT Technologies Inc., a software design company, says it has been able to overcome the mask-wearing difficulty associated with face biometrics.
The company filed a patent for a computer and mobile-based AI facial recognition system with computer vision algorithms that can learn users’ features, such as facial and body changes, with or without masks or clothing, via one-time user enrollment. The system could be used in smartphones’ biometric password features, to measure aspects of health, or for security and law enforcement in identifying persons of interest in airports with or without face masks in real-time.
Leveraging AI, the algorithm can learn users’ skull size, skeleton shape, body size, eye distance, and bone structure. The system may also include a mobile application software and server backend programs.
A passcode can still be used on the phone or computer if preferred, according to the patent application.
“The security of our electronic devices has become a major challenge in the past decade as we witness a significant increase in cybercrimes. As we are working on our health monitoring hardware and software technology, we aim to provide the highest level of data security and privacy for our users,” stated Danny Rittman, GBT’s CTO.
“We measure facial and bodily points distances and transform them into a 3D point figure using internal calibration algorithms…We plan to evaluate further applications for this type of technology like health watcher system, fitness monitoring, airport security and law enforcement,” Rittman added.
The company notes that implementing the biometric technology will require further research and development and a manufacturing partnership, among other steps.