Daon Holdings Limited

Mircea Ionita

Michael Peirce

James Ahern

Michael Stephen Watson

A method for verifying the identity of a user is provided that includes generating, by a computing device, a parameter for each processed frame in a video of biometric data captured from a user. The parameter results from movement of the computing device during capture of the biometric data. Moreover, the method includes generating a signal for the parameter and calculating a confidence score based on the generated signal and a classification model specific to the user. The classification model is generated from other signals generated for the parameter. Furthermore, the method includes verifying the identity of the user as true when the confidence score is at least equal to a threshold score.

Methods and systems for determining user liveness and verifying user identities

A method for detecting user liveness is provided that includes selecting first and second images from a sequence of images. The first and second images are captured under different illumination conditions. The method further includes locating feature calculation windows in corresponding positions on the first and second images. Each window includes a first area and a second area. Moreover, the method includes calculating, by a computing device, a feature value for each window position based on pixels, within the windows located at the position, from the first and second images. Furthermore, the method includes calculating a feature vector from the feature values, calculating a confidence score from the feature vector, and determining the sequence of images includes images of a live user when the confidence score is equal to or greater than the threshold score.

Methods and systems for detecting user liveness

A method for capturing image data of a user is provided that includes displaying, by a computing device, a perspective view of a virtual computing device. Moreover, the method includes changing, by the computing device, the perspective view of the virtual computing device while the computing device moves, changing, by the computing device, the display of the virtual computing device to provide notification that the computing device is in an acceptable position for capturing image data of a user, and capturing, by a camera included in the computing device, facial image data of the user.

Methods and systems for capturing image data

A method for enhancing user liveness detection is provided that includes calculating, by a computing device, parameters for each frame in a video of captured face biometric data. Each parameter results from movement of at least one of the computing device and the biometric data during capture of the biometric data. The method also includes creating a signal for each parameter and calculating a similarity score. The similarity score indicates the similarity between the signals. Moreover, the method includes determining the user is live when the similarity score is at least equal to a threshold score.

Methods and systems for enhancing user liveness detection

A method for enhancing user liveness detection is provided that includes calculating, by a computing device, a first angle and a second angle for each frame in a video of captured face biometric data. The first angle is between a plane defined by a front face of the terminal device and a vertical axis, and the second angle is between the plane defined by the front face of the terminal device and a plane defined by the face of the user. Moreover, the method includes creating a first signal from the first angles and a second signal from the second angles, calculating a similarity score between the first and second signals, and determining the user is live when the similarity score is at least equal to a threshold score.

A method of authenticating users is provided that includes storing data in a buffer. The data is within a temporal window and includes biometric data extracted from frames included in a video and quality feature values calculated for each frame. Each quality feature value corresponds to a different quality feature. Moreover, the method includes calculating a score for each different quality feature using the corresponding quality feature values, and determining a most recent frame included in the video includes biometric data usable in a biometric authentication matching transaction when the calculated score for each different quality feature satisfies a respective threshold score value.

Methods and systems for authenticating users

A method determining user liveness is provided that includes calculating, by a device, eye openness measures for a frame included in captured authentication data, and storing the eye openness measures in a buffer of the device. Moreover the method includes calculating confidence scores from the eye openness measures stored in the buffer, and detecting an eye blink when a maximum confidence score is greater than a threshold score.

Methods and systems for determining user liveness

A method for detecting biometric characteristics in a captured biometric data image is provided that includes determining, by a processor, an approximate location for a biometric characteristic in a frame included in captured biometric data, and determining region of interest positions over the frame. Moreover, the method includes calculating a set of feature values for each position, generating a displacement for each set of feature values and generating a median displacement, and adjusting the biometric characteristic location by the median displacement.

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Dublin, Ireland

Mircea Ionita