Abstract: One implementation involves a device receiving a stream of pixel events output by an event camera. The device derives an input image by accumulating pixel events for multiple event camera pixels. The device generates a gaze characteristic using the derived input image as input to a neural network trained to determine the gaze characteristic. The neural network is configured in multiple stages. The first stage of the neural network is configured to determine an initial gaze characteristic, e.g., an initial pupil center, using reduced resolution input(s). The second stage of the neural network is configured to determine adjustments to the initial gaze characteristic using location-focused input(s), e.g., using only a small input image centered around the initial pupil center. The determinations at each stage are thus efficiently made using relatively compact neural network configurations. The device tracks a gaze of the eye based on the gaze characteristic.

Abstract: A method and authentication system for alleviating authenticity of sensors in biometric authentication is disclosed. The authentication system receives fingerprint data from a plurality of sensing devices configured in the authentication system and extract one or more attributes associated with the fingerprint data. An expanded value for each of the one or more attributes is determined based on one or more predefined techniques. The authentication system (101) trains a model associated with authentication of fingerprints using the one or more attributes and corresponding expanded value. Further, one or more errors associated with the fingerprint data are predicted based on fingerprint data received over a period of time in real-time and the model is retrained based on the predicted one or more errors to alleviate authenticity of sensors in biometric authentication.

Abstract: A method for fingerprint authentication according to an embodiment of the present disclosure includes, in response to receiving an authentication request, performing fingerprint image acquisition and comparison of a first mode, and selectively performing fingerprint image acquisition and comparison of a second mode, and performing authentication at least based on a comparison result of the first mode. In the first mode, a fingerprint image generated by a pressing operation of a target finger in a fingerprint acquisition area is acquired, and in the second mode, a fingerprint image sequence generated by a sliding operation of the target finger in the fingerprint acquisition area is acquired. A selective fingerprint authentication security mode can be provided as needed, so as to meet various authentication requirements.

Abstract: An electronic device includes a display panel including at least one light source, a point detector disposed on one surface of the display panel or inside the display panel, and at least one processor operatively connected with the display panel and the point detector. The at least one processor is configured to cause the at least one light source to emit light in response to an object outside the display panel, detect, through the point detector, at least a portion of the emitted light reflected by at least a portion of the object, and obtain biometric information corresponding to the object based on the detection.

Abstract: Provided is an identification method for an identification system, which includes a sensing area and an image sensor. First, a test object is close to the sensing area, so that the image sensor generates a dynamic image. Next, the test object gradually pressurizes the sensing area. Then, the test object completely covers the sensing area, and the image sensor further produces a perspective image. Finally, an identification module is used to determine whether the dynamic image is a biological image according to the perspective image, and to perform a subtraction operation on the dynamic image as a basis to determine whether to unlock the identification system. Therefore, the identification system and the identification method can achieve a real-time determination on whether the dynamic image is a biological image. Also, the identification method greatly improves the false acceptance rate (FAR) and the false rejection rate (FRR) of the identification system.

Abstract: A fingerprint sensing module is used for a liquid crystal display (LCD) panel having a sensing area. The fingerprint sensing module includes a light source and a shielding frame. The light source is configured to provide light emission for fingerprint sensing performed on the sensing area, wherein the sensing area is at a first side of the light source. The shielding frame is disposed on a light emission path from the light source toward the first side.

Abstract: An in-screen fingerprint identification apparatus includes a display panel and a fingerprint identification module. The display panel includes a backlight module, a liquid crystal layer, and a cover glass, which are sequentially stacked. The cover glass includes a fingerprint identification area. The fingerprint identification module includes a light source, a photosensor, and light guiding layers disposed on the cover glass. The light guiding layers at least cover portions of opposite sides of the cover glass, respectively, such that light emitted by the light source after being reflected in the cover glass is guided to the fingerprint identification area. The photosensor is disposed in the display panel and corresponds to the fingerprint identification area to receive an optical signal of the light source emitted by the light source after being reflected by a finger in the fingerprint identification area.

Abstract: A technique for accurately extracting a fingerprint image for accurate authentication from 3D tomographic luminance data of a finger at a high speed. A processing apparatus (11) according to the present disclosure includes means for, after performing edge detection processing on a tomographic image (101, 102, . . . 10 k, . . . , 10n) at each depth, calculating the total number of edge pixels in the tomographic image from 3D (three-dimensional) tomographic luminance data, and acquiring depth dependence of the number of edges (111, 112), and means for extracting a tomographic image having a striped pattern from the depth dependence of the number of edges and the 3D tomographic luminance data.

Abstract: There is provided an electronic apparatus, and an improved design flexibility and minimized power consumption for biometric authentication in an electronic apparatus that performs biometric authentication, the electronic apparatus including: a wearable part movable to be worn on a user's body; and a biometric information acquisition unit provided on the wearable part and configured to acquire biometric information of the user for user authentication. This configuration makes it possible to improve design flexibility and minimize power consumption for biometric authentication in an electronic apparatus that performs biometric authentication.

Abstract: A biometrics-enabled portable storage device may store and secure data via biometrics related to a user's iris. The biometrics-enabled portable storage device may include a camera that captures image data related a user's iris and stores the image data to enroll the user for use of the biometrics-enabled portable storage device. To unlock the data, a user aligns the camera with their iris using a hot mirror and the camera captures iris data for comparison with the iris image data stored during enrollment. If the two sets of image data match, the biometrics-enabled portable storage device may be unlocked and the user may access data stored on the biometrics-enabled portable storage device. If the two sets of image data do not match, then the biometrics-enabled portable storage device remains locked.

Abstract: The present disclosure relates to a method of controlling an electronic device, the electronic device comprising a fingerprint sensor. The present disclosure also relates to a corresponding electronic device and to a computer program product.

Abstract: The present disclosure provides an ultrasonic sensor pixel circuit, a driving method thereof and a display panel. The ultrasonic sensor pixel circuit includes a detection module, of which a first terminal is connected with an ultrasonic sensing unit and a second terminal is connected with a first signal terminal, and the detection module is configured to generate a detection voltage according to an electric signal output from the ultrasonic sensing unit under control of the first signal terminal; an output module, of which a first terminal is connected with a third terminal of the detection module and a second terminal is connected with a read line, and the output module is configured to generate an output signal according to the detection voltage and provide the output signal to the read line.

Abstract: An action evaluation model building apparatus and an action evaluation model building method thereof are provided. The action evaluation model building apparatus stores a plurality of raw data sets and a plurality of standard action labels corresponding thereto. Based on machine learning algorithms, the action evaluation model building apparatus computes the raw data sets and performs a supervised learning to build a feature vector creation model and a classifier model. The action evaluation model building apparatus determines a representation action feature vector of each standard action label by randomly generating a plurality of action feature vectors and inputting them into the classifier model. The action evaluation model building apparatus builds an action evaluation model based on the feature vector creation model, the classifier model and the representation action feature vectors.

Abstract: A method for acquiring a fingerprint image through a fingerprint image acquisition apparatus is provided. The method includes recognizing a finger of an user through a sensor included in the apparatus to generate an initial input fingerprint image when the finger contacts with a biometric recognition area of the display unit, acquiring a converted fingerprint image by converting the initial input fingerprint image in a pre-determined manner to reveal a characteristic of a pattern, included within the initial input fingerprint image, corresponding to a pattern signal reflected from at least a part of the display unit. The method further includes selecting a pattern removal fingerprint image, if a learned pattern image is stored in a memory, from the learned pattern image based on similarity. The similarity is calculated between the converted fingerprint image and a converted reference image.

Abstract: An information processor including a sensor unit that recognizes an operating tool that comes into contact with a display unit, and a control unit that shows a guidance display for guiding an operation of the operating tool on the display unit.

Abstract: The present disclosure teaches a method of utilizing image “match points” to measure and detect changes in a physical object. In some cases “degradation” or “wear and tear” of the physical object is assessed, while in other applications this disclosure is applicable to measuring intentional changes, such as changes made by additive or subtractive manufacturing processes, which may, for example, involve adding a layer or removing a layer by machining. A system may include a scanner, and a digital fingerprinting process, coupled to an object change computer server. The server is coupled to a datastore that stores class digital fingerprints, selected object digital fingerprints collected over time, match measurements, and deterioration metrics.

Abstract: The present disclosure provides a display module, and a display method and a terminal thereof, in the field of display technology. The display module includes a display panel and a control circuit; wherein the control circuit is configured to control a target region on the display panel to display a target image when the display panel is in an off-screen state, and the target region includes a fingerprint collection region. The present disclosure solves the problem that fingerprint collection operations on the terminal in the related art are complicated, and reliability is poor. The present disclosure is for fingerprint collection.

Abstract: A method of completing a task, the task being of a given type of task. The method includes receiving, by a server, an indication of a first result of the task having been completed by a human assessor, executing by the server a machine learning algorithm (MLA) to complete the task by the MLA to generate a second result of the task, determining, by the server, a confidence level parameter indicative of a probability of the first result being correct, and determining, by the server, whether the probability indicated by the determined confidence level parameter exceeds a pre-defined threshold probability. In response to determining that the probability indicated by the determined confidence level parameter exceeds the pre-defined threshold probability, the server processes the task as having been completed with the first result.

Abstract: Embodiments of the present application provide a lens system, a finger identification apparatus and a terminal device, including a first lens, a second lens and a third lens arranged sequentially from an object side to an image side, where the first lens is a S-shaped meniscus negative optical power lens, the second lens is a biconvex positive optical power lens and a focal length of the first lens and a focal length of the second lens follow a first relationship so that a field of view (FOV) is greater than a first threshold.

Abstract: Methods and systems for of generating reporting data in an automated, efficient, and risk-free fashion relating to an identification match relating to a probe image are disclosed. Methods include automatically capturing a comparison area in the probe image and a comparison area of a candidate image based on examiner input; facilitating a determination of whether a similarity or a dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image; automatically recording metadata based on the determination of whether the similarity or the dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image and updating an audit log; and generating a report comprising the metadata.