$GTCH with GBT Tokenize Corp. (“GBT/Tokenize”)
Post# of 53480
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Posted On: 03/31/2021 7:54:27 AM
$GTCH with GBT Tokenize Corp. (“GBT/Tokenize”) filed with U.S. Patent and Trademark Office (“USPTO”) a nonprovisional patent for systems and methods of facial and body recognition identification and analysis. The application has been assigned serial number 17212235 and the filing date is March 25, 2021. As a reminder the Company advised on its release from February 16, that the deadline for filing a U.S. nonprovisional, PCT, or other foreign applications is February 9, 2022.
The present invention relates to systems and methods for learning and recognizing features of an image such as a human face and unlocking functions for any computer or smartphone screen based on facial and body recognition, including covered face or body.
Many mobile devices such as smartphones include a facial identification (ID) recognition system that learns the user’s facial features and unlocks the phone upon its user’s face image. Due to the COVID-19 pandemic, in most public places a face cover or facemask is required. However, the presence of a face cover or mask interrupts the face recognition unlocking feature on most mobile devices. Accordingly, there is a need for a system and method that can learn and recognize a partially covered human face and method that can unlock a mobile device based on recognition of a partially covered human face.
The invention, in its many embodiments, alleviates to a great extent the disadvantages of known devices, systems, and methods by providing an AI-based computer vision systems and methods to lock and unlock a mobile device such as a smartphone with or without face (mask) coverage. The user trains the system once without a face cover (mask). After the initial training, the system is capable of identifying the user’s facial features with or without a face cover or facemask, and is capable of locking or unlocking a smartphone/electronic device. After learning the user’s body’s features, the system can monitor bodily changes like weight gain and other changes, alerting the user in real time.
The present invention relates to systems and methods for learning and recognizing features of an image such as a human face and unlocking functions for any computer or smartphone screen based on facial and body recognition, including covered face or body.
Many mobile devices such as smartphones include a facial identification (ID) recognition system that learns the user’s facial features and unlocks the phone upon its user’s face image. Due to the COVID-19 pandemic, in most public places a face cover or facemask is required. However, the presence of a face cover or mask interrupts the face recognition unlocking feature on most mobile devices. Accordingly, there is a need for a system and method that can learn and recognize a partially covered human face and method that can unlock a mobile device based on recognition of a partially covered human face.
The invention, in its many embodiments, alleviates to a great extent the disadvantages of known devices, systems, and methods by providing an AI-based computer vision systems and methods to lock and unlock a mobile device such as a smartphone with or without face (mask) coverage. The user trains the system once without a face cover (mask). After the initial training, the system is capable of identifying the user’s facial features with or without a face cover or facemask, and is capable of locking or unlocking a smartphone/electronic device. After learning the user’s body’s features, the system can monitor bodily changes like weight gain and other changes, alerting the user in real time.
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