There is provided an information acquisition apparatus including an output means for outputting guidance information for guiding a subject to move a head while gazing at a predetermined position, and an image acquisition means for acquiring an image including an iris of the subject after outputting the guidance information.

Described herein are computer-implemented methods for identifying and classifying one or more regions of interest in a facial region and augmenting an appearance of the regions of interest in an image. For example, a region of interest may include one or more of: a teeth region, a lip region, a mouth region, or a gum region. User selected templates for teeth, gums, smile, etc. may be used to replace the analogous facial features in an input image provided by the user, for example from an image library or taken with an image sensor. The computer-implemented methods described herein may use one or more trained machine learning models and one or more algorithms to identify and classify regions of interest in an input image.

Embodiments relate to systems, methods and computer readable media for gaming monitoring. In particular, embodiments process images to determine presence of a gaming object on a gaming table in the images. Embodiments estimate postures of one or more players in the images and based on the estimated postures determine a target player associated with the gaming object among the one or more players.

Exemplary embodiments of this disclosure provide a living body detection method and apparatus, an electronic device, a storage medium, and a payment system, a video surveillance system, and an access system to which the living body detection method is applied, and generally belong to the field of biometric recognition technologies. The living body detection method can include obtaining an image of a to-be-detected object performing key point detection on a biometric feature corresponding to the to-be-detected object in the image, and constructing a constraint box in the image according to detected key points. Further, the method can include capturing a shape change of the constraint box constructed in the image, and determining the to-be-detected object as a prosthesis in response to capturing an abnormal deformation of the constraint box or detecting no key points.

Systems, devices, media, and methods are presented for presentation of modified objects within a video stream. The systems and methods receive a set of images within a video stream and identify at least a portion of a face in a first subset of images. The systems and methods determine face characteristics by analyzing the portion of the face in the first subset of images. The systems and methods apply a graphical representation of glasses to the face based on the face characteristics and cause presentation of a modified video stream including the portion of the face with the graphical representation of the glasses in a second subset of images of the set of images while receiving the video stream.

A video detection device includes a video acquisition interface, a video recognition interface, and a tilt angle estimation interface. The video acquisition interface acquires a video of the face of an imaging subject. The video recognition interface recognizes the left and right eyes from the video acquired by the video acquisition interface. The tilt angle estimation interface estimates a tilt angle with respect to the horizontal based on the position of the left and right eyes recognized by the video recognition interface.

An electronic device includes: a camera; a microphone; a display; a memory; and a processor configured to receive an input for activating an intelligent agent service from a user while at least one application is executed, identify context information of the electronic device, control to acquire image information of the user through the camera, based on the identified context information, detect movement of a user's lips included in the acquired image information to recognize a speech of the user, and perform a function corresponding to the recognized speech.

There is provided a method for predicting characteristic information of a target to be recognized. The method comprises: acquiring a plurality of first face images for learning and characteristic information on each first face image; generating a plurality of second face images for learning obtained by synthesizing a mask image with the plurality of first face images for learning by a predetermined algorithm; and training a first neural network by using the plurality of second face images for learning as input data for learning and characteristic information as label data for each second face image corresponding to one of the first face images.

In an embodiment, a virtual reality ride system includes a display to present virtual reality image content to a first rider, an audio sensor to capture audio data associated with a second rider, and an image sensor to capture image data associated with the second rider. The virtual reality ride system also includes at least one processor communicatively coupled to the display and configured to (i) receive the audio data, the image data, or both, (ii) generate a virtual avatar corresponding to the second rider, wherein the virtual avatar includes a set of facial features, (iii) update the set of facial features based on the audio data, the image data, or both, and (iv) instruct the display to present the virtual reality image content including the virtual avatar and the updated set of facial features.

Systems and methods are disclosed for determining textual transcription from minute facial skin movements. In one implementation, a system may include at least one coherent light source, at least one sensor configured to receive light reflections from the at least one coherent light source; and a processor configured to control the at least one coherent light source to illuminate a region of a face of a user. The processor may receive from the at least one sensor, reflection signals indicative of coherent light reflected from the face in a time interval. The reflection signals may be analyzed to determine minute facial skin movements in the time interval. Then, based on the determined minute facial skin movements in the time interval, the processor may determine a sequence of words associated with the minute facial skin movements, and output a textual transcription corresponding with the determined sequence of words.