Abstract: A method is provided for evaluating an effect of classifying a fuzzy attribute of an object, the fuzzy attribute referring to an attribute, a boundary between two similar ones of a plurality of categories of which is blurred, wherein the method includes: generating a similarity-based ranked confusion matrix, which comprises: based on similarities of K categories of the fuzzy attribute of the object, ranking the K categories, where K is an integer greater than or equal to 2, generating a K×K all-zero initialization matrix, wherein an abscissa and an ordinate of the initialization matrix respectively represent predicted values and true values of the similarity-based ranked categories of the fuzzy attribute, and based on the true values and the predicted values of the category of the fuzzy attribute for the multiple object samples, updating values of corresponding elements in the initialization matrix; and displaying the similarity-based ranked confusion matrix.

Abstract: There is described a deep learning supervised regression based model including methods and systems for facial attribute prediction and use thereof. An example of use is an augmented and/or virtual reality interface to provide a modified image responsive to facial attribute predictions determined from the image. Facial effects matching facial attributes are selected to be applied in the interface.

Abstract: This disclosure describes techniques to aggregate sensor data. The techniques perform operations comprising: receiving, from a first sensor, a first profile representing a first set of movement attributes detected by the first sensor in an area at a given point in time; receiving, from a second sensor, a second profile representing a second set of movement attributes detected by the second sensor in the area at the given point in time; computing a similarity measure between the first and second sets of movement attributes of the first and second profiles; determining that the similarity measure exceeds a threshold value; and in response to determining that the similarity measure exceeds the threshold value, associating the first and second profiles with a same first object that is in the area at the given point in time.

Abstract: A method for controlling an ego agent includes capturing a two-dimensional (2D) image of an environment adjacent to the ego agent. The method also includes generating a semantically segmented image of the environment based on the 2D image. The method further includes generating a depth map of the environment based on the semantically segmented image. The method additionally includes generating a three-dimensional (3D) estimate of the environment based on the depth map. The method also includes controlling an action of the ego agent based on the identified location.

Abstract: The disclosure herein describes systems and methods for object data storage. In some examples, the method includes generating a profile for an object in a directory, the profile including a first feature vector corresponding to the object and a global unique identifier (GUID) corresponding to the first feature vector in the profile; generating a search scope, the search scope including at least the GUID corresponding to the profile; generating a second feature vector from a live image scan; matching the generated second feature vector from the live image scan to the first feature vector using the generated search scope; identifying the GUID corresponding to the first feature vector that matches the second feature vector; and outputting information corresponding to the object of the profile identified by the GUID corresponding to the first feature vector.

Abstract: Methods, systems and computer readable medium for liveness detection authentication of a facial image are provided. The method includes acquiring a first image of the facial image illuminated with a first color, acquiring a second image of the facial image illuminated with a second color, and determining if the facial image is consistent with a three-dimensional (3D) structure in response to a combination of the first and second images. The method further includes authenticating the facial image if the facial image is consistent with a 3D structure and the facial image matches a face of user to be authenticated.

Abstract: An image processing method executed by a computer, the method includes detecting a plurality of feature points of a face from an input image, referring to importance information that indicates an importance of a region within an image in a process of detecting a predetermined facial motion from the image, selecting, from the plurality of feature points detected by the detecting, one or more points that correspond to an image region including an importance indicated by the importance information equal to or smaller than a first threshold value, correcting the input image by using the one or more points selected by the selecting, to generate a corrected image; and determining whether or not the predetermined facial motion is occurring in the input image, based on an output obtained by inputting the corrected image to a recognition model.

Abstract: A method of host-directed illumination for verifying the validity of biometric data of a user is provided that includes capturing biometric data from a user with an authentication device during authentication and directing illumination of the biometric data from a host authentication system during the capturing operation. Moreover, the method includes comparing illumination characteristics of the captured biometric data against illumination characteristics expected to result from the directing operation, and determining that the user is a live user when the illumination characteristics of the captured biometric data match the illumination characteristics expected to result from the directing operation.

Abstract: One embodiment of the present invention sets forth a technique for performing spatial propagation. The technique includes generating a first directed acyclic graph (DAG) by connecting spatially adjacent points included in a set of unstructured points via directed edges along a first direction. The technique also includes applying a first set of neural network layers to one or more images associated with the set of unstructured points to generate (i) a set of features for the set of unstructured points and (ii) a set of pairwise affinities between the spatially adjacent points connected by the directed edges. The technique further includes generating a set of labels for the set of unstructured points by propagating the set of features across the first DAG based on the set of pairwise affinities.

Abstract: Disclosed is a facial recognition system/method, utilizing modules to perform the following routine: extracting a feature descriptor from a detected feature point of a detected face in an input image frame; and matching the extracted feature descriptor with at least one of a pre-stored facial image that is index-mapped, comprising at least a first and second round of matching, wherein the second round of matching only selects the index-mapped facial images that matched above a pre-defined threshold from the first round of matching. Optionally, the above described steps may be coupled to a Point-of-Recognition (POR) provisioning, enabling an on-demand gate-keeping and/or payment processing for an end-user at an event/venue entry or point-of-sale.

Abstract: An example method includes obtaining, by processing circuitry, an image depicting a face of a person wearing eyewear and a reflection pattern generated by projecting light onto a lens of the eyewear and determining, by the processing circuitry, an optical parameter of the lens based on the image. The method further includes receiving, by the processing circuitry and from an electronic database, a personal characteristic data relating to a previously identified person and comparing, by the processing circuitry, the optical parameter of the lens to the personal characteristic data. The method further includes determining, by the processing circuitry and based on the comparison, a score indicative of a match between the person wearing eyewear and the previously identified person.

Abstract: The present disclosure describes systems and methods for image processing. Embodiments of the present disclosure include an image processing apparatus configured to generate modified images (e.g., synthetic faces) by conditionally changing attributes or landmarks of an input image. A machine learning model of the image processing apparatus encodes the input image to obtain a joint conditional vector that represents attributes and landmarks of the input image in a vector space. The joint conditional vector is then modified, according to the techniques described herein, to form a latent vector used to generate a modified image. In some cases, the machine learning model is trained using a generative adversarial network (GAN) with a normalization technique, followed by joint training of a landmark embedding and attribute embedding (e.g., to reduce inference time).

Abstract: Security on an information handling system may be improved by using a stylus. A stylus provides unique information about a user that may not be acquired by an information handling system through other methods. For example, a user's handwriting is often unique to that user and may provide a security check on the information handling system to confirm the user's identity. Further, the stylus is usually held in the user's hand and may be used to check the user's fingerprint to confirm the user's identity. These authentication techniques, including fingerprinting and handwriting, may be used to maintain persistent authentication while the user is using the stylus. As the user continues to interact with the information handling system with the stylus, the stylus continues to receive the user's fingerprint and handwriting, which may be checked to confirm the user of the information handling system is still the expected user.

Abstract: A display module and a manufacturing method thereof are provided. The display module includes a display panel and a fingerprint identification module disposed in the display panel, wherein the display panel includes a first substrate, a second substrate located above the first substrate, and a functional layer prepared and disposed above the second substrate, and the fingerprint identification module is disposed between the first substrate and the second substrate. The present application realizes a technical effect of a simplified manufacturing process of the display module and an overall simple structure through integrating the fingerprint identification module into the display panel.

Abstract: A method of training a fingerprint image enhancing engine for use in a fingerprint capturing device, and a corresponding apparatus and computer readable medium, include producing a synthetic image dataset comprising plural pairs of synthetic images. Each pair of synthetic images include a clean synthetic image and a raw synthetic image corresponding to the clean synthetic image. Each raw synthetic image is produced according to a model of the fingerprint capturing device. The method also includes training a neural network using the synthetic image dataset.

Abstract: In one embodiment, a sensor system includes an active thermal sensor pixel matrix, a plurality of presence sensors, and an image acquisition controller. The pixel matrix includes a plurality of pixels arranged in a plurality of rows and a plurality of columns and a boundary defining a perimeter. The plurality of presence sensors is disposed at least partially within the boundary of the pixel matrix. The image acquisition controller is coupled to the pixel matrix and the plurality of presence sensors. The image acquisition controller is configured to: (i) receive signals from the presence sensors; (ii) identify, based on the signals, a scan region, wherein the scan region is a portion of the pixel matrix that is in contact with or adjacent to a specimen; and (iii) obtain image data only from pixels that are within the scan region for generating an image of the specimen.

Abstract: The present disclosure provides a display substrate and a display device, and belongs to the field of display technology. The display substrate of the present disclosure includes: a base substrate having a display region; a plurality of fingerprint identification circuits in the display region of the base substrate, wherein each fingerprint identification circuit includes a control sub-circuit and a detection electrode; wherein in a fingerprint identification phase, the control sub-circuit is configured to read a capacitance between the detection electrode and a valley and a ridge of a fingerprint in response to a fingerprint scanning signal, so as to perform fingerprint identification.

Abstract: System and method for voice-face matching, including: obtaining a voice sample, a first facial image of a first person, and a second facial image of a second person; calculating a distance between the first facial image and the second facial image; using a voice-face matching model, calculating a latent space vector for each of the voice sample and the first and second facial images; and training the voice-face matching model using a loss function that decreases a distance between the latent space vector of the voice sample of the first person and the latent space vector of the first facial image, and increases a distance between the latent space vector of the voice sample of the first person and the latent space vector of the second facial image, wherein the loss function is adjusted based on the distance between the first facial image and the second facial image.

Abstract: Disclosed is a system for face recognition based on dynamic updating of facial features, comprising an image acquisition unit, a face image standardization unit, a facial feature comparison unit, and a facial feature update unit. The image acquisition unit acquires an original image which is processed by the face image standardization unit, and then the facial feature comparison unit completes extraction and comparison of a facial feature vector to determine whether the original image belongs to a user ID or a stranger, or to complete entry of the facial feature vector. Each user ID corresponds to one or more facial feature vectors. The facial feature update unit automatically updates the facial feature vector in a normal workflow to improve reliability and accuracy of face recognition. Also disclosed is a method for face recognition using the system.

Abstract: The objective is to achieve highly accurate authentication even when there is variation in the ambient light environment during biometric imaging. A biometric authentication device includes an image capturing unit that captures images of a living body, a light source for capturing images of the living body, an optical filter that selectively passes and blocks light according to wavelength, a spectroscopic processing unit that separates multiple wavelengths captured simultaneously, respectively, and a calculation unit that calculates the shape and posture of a predetermined part of the living body in the captured images, a background removal unit that removes the background from the image of the living body using the spectral images of the living body and the spectral image of the unwanted ambient light, and an authentication unit that performs biometric authentication using the image of the predetermined part.