Abstract:
Provided is a user authentication method and apparatus that obtains first environmental information indicating an environmental condition in which an input image of a user is captured, extracts a first feature vector from the input image, selects a second feature vector including second environmental information that matches the first environmental information from enrolled feature vectors in an enrollment database (DB), and authenticates the user based on the first feature vector and the second feature vector.
Abstract:
A face verifying method and apparatus. The face verifying method includes detecting a face region from an input image, generating a synthesized face image by combining image information of the face region and reference image information, based on a determined masking region, extracting one or more face features from the face region and the synthesized face image, performing a verification operation with respect to the one or more face features and predetermined registration information, and indicating whether verification of the input image is successful based on a result of the performed verification operation.
Abstract:
Disclosed is a user recognition apparatus and method, the apparatus configured to determine a validity of an iris area for each frame, to perform an iris recognition when the iris area is valid, and to extract a facial feature for a fusion recognition when the iris area is invalid.
Abstract:
A method to reduce a neural network includes: adding a reduced layer, which is reduced from a layer in the neural network, to the neural network; computing a layer loss and a result loss with respect to the reduced layer based on the layer and the reduced layer; and determining a parameter of the reduced layer based on the layer loss and the result loss.
Abstract:
A neural network recognition method includes obtaining a first neural network that includes layers and a second neural network that includes a layer connected to the first neural network, actuating a processor to compute a first feature map from input data based on a layer of the first neural network, compute a second feature map from the input data based on the layer connected to the first neural network in the second neural network, and generate a recognition result based on the first neural network from an intermediate feature map computed by applying an element-wise operation to the first feature map and the second feature map.
Abstract:
A method and apparatus for estimating a pose that estimates a pose of a user using a depth image is provided, the method including, recognizing a pose of a user from a depth image, and tracking the pose of the user using a user model exclusively of one another to enhance precision of estimating the pose.
Abstract:
A display information controlling apparatus and method are provided. The display information controlling apparatus may select at least one object from one or more objects based on a location of each of the one or more objects on a display and a location on the display corresponding to a user input signal. The display information controlling apparatus may perform a predetermined operation corresponding to the selected at least one object.
Abstract:
A method of displaying a menu based on at least one of a depth information and a space gesture is provided. The method including determining depth information corresponding to a distance from a screen of a user terminal to a hand of a user; identifying at least one layer among a plurality of layers based on the depth information; and applying a graphic effect to the identified layer so that a menu page corresponding to the at least one identified layer is displayed on the screen of the user terminal.
Abstract:
Provided is a calibration apparatus and method of a three-dimensional (3D) position and direction estimation system. The calibration apparatus may receive inertia information and intensity information during a predetermined period of time, may calculate distances between a transmitter and the respective receivers, and may calibrate a signal attenuation characteristic of each receiver using the distances between the transmitter and the respective receivers.
Abstract:
Provided is a method of creating a body pose cluster, including performing feature extraction from pose data about at least one pose, classifying, as a single cluster, similar poses from a feature vector space using a similarity measure, and configuring the number of poses included in each cluster from the feature vector space to be uniform using an imbalance measure.