Abstract: One embodiment can provide a system for authenticating an object. During operation, the system configures an environment surrounding the object according to one or more target environmental factors, captures at least a first image of the object while the object is exposed to the target environmental factors, and determines Fan authenticity of the object based on the captured first image and the target environmental factors.

Abstract: Embodiments described herein provide a system for facilitating entity recognition. During operation, a camera associated with a computing device captures at least a first image of a to-be-recognized entity under a first imaging condition. The system adjusts the first imaging condition to achieve a second imaging condition, and the camera captures at least a second image under the second imaging condition. The system determines whether the to-be-recognized entity is a physical entity based on the captured first and second images and the first and second imaging conditions.

Abstract: One embodiment facilitates identification of re-photographed images. During operation, the system obtains a sequence of video frames of a target object. The system selects a frame with an acceptable level of quality. The system obtains, from the selected frame, a first image and a second image associated with the target object, wherein at least one of a zoom ratio property and a size property is different between the first image and the second image. The system inputs the first image and the second image to at least a first neural network to obtain scores for the first image and the second image, wherein a respective score indicates a probability that the corresponding image is re-photographed, wherein a re-photographed image is obtained by photographing or recording an image of the target object. The system indicates the selected frame as re-photographed based on the obtained probabilities.

Abstract: Provided is a 3D registration method and apparatus that may select a key point from among plural points included in 3D target data, based on a geometric feature or a color feature of each of the plural points, may adjust a position of the selected key point of the 3D target data based on features of, or a distance between, a key point of the 3D source data and the selected key point of the 3D target data, may calculate reliabilities of plural key points of the 3D source data based on respective features of at least one key point of the 3D target data determined to correspond to the plural key points of the 3D source data, and may generate 3D registration data by performing 3D registration between the 3D source data and the 3D target data based on the calculated reliabilities.

Abstract: Embodiments described herein provide a system for facilitating entity recognition. During operation, a camera associated with a computing device captures at least a first image of a to-be-recognized entity under a first imaging condition. The system adjusts the first imaging condition to achieve a second imaging condition, and the camera captures at least a second image under the second imaging condition. The system determines whether the to-be-recognized entity is a physical entity based on the captured first and second images and the first and second imaging conditions.

Abstract: One embodiment can provide a system for authenticating an object. During operation, the system configures an environment surrounding the object according to one or more target environmental factors, captures at least a first image of the object while the object is exposed to the target environmental factors, and determines Fan authenticity of the object based on the captured first image and the target environmental factors.

Abstract: One embodiment facilitates identification of re-photographed images. During operation, the system obtains a sequence of video frames of a target object. The system selects a frame with an acceptable level of quality. The system obtains, from the selected frame, a first image and a second image associated with the target object, wherein at least one of a zoom ratio property and a size property is different between the first image and the second image. The system inputs the first image and the second image to at least a first neural network to obtain scores for the first image and the second image, wherein a respective score indicates a probability that the corresponding image is re-photographed, wherein a re-photographed image is obtained by photographing or recording an image of the target object. The system indicates the selected frame as re-photographed based on the obtained probabilities.

Abstract: Embodiments described herein provide a system for facilitating liveness detection of a user. During operation, the system presents a verification interface to the user in a local display device. The verification interface includes one or more phrases and a reading style for a respective phrase in which the user is expected to recite the phrase. The system then obtains a voice signal based on the user's recitation of the one or more phrases via a voice input device of the system and determines whether the user's recitation of a respective phrase has complied with the corresponding reading style. If the user's recitation of a respective phrase has complied with the corresponding reading style, the system establishes liveness for the user.

Abstract: A biometric authentication apparatus and method are provided. The biometric authentication apparatus may obtain at least two types of biosignals, extract a same type of physiological features from each of the biosignals, and determine whether the biosignals are generated from a same living body based on the extracted same type of physiological features.

Abstract: A method and an apparatus for adjusting a pose in a face image are provided. The method of adjusting a pose in a face image involves detecting two-dimensional (2D) landmarks from a 2D face image, positioning three-dimensional (3D) landmarks in a 3D face model by determining an initial pose of the 3D face model based on the 2D landmarks, updating the 3D landmarks by iteratively adjusting a pose and a shape of the 3D face model, and adjusting a pose in the 2D face image based on the updated 3D landmarks.

Abstract: Disclosed are an electrocardiogram (ECG) authentication method and apparatus, and a training method and apparatus for training a neural network model used for ECG authentication, the ECG authentication apparatus being configured to acquire an ECG signal of a subject, extract a semantic feature of the ECG signal, and authenticate the subject based on the extracted semantic feature.

Abstract: Provided are electrocardiogram (ECG)-based authentication and training. An authentication method includes generating a feature vector of an ECG obtained from an entity or a person based on a dictionary, classifying the ECG through a classifier based on the feature vector, and performing authentication based on a classification result.

Abstract: Provided are a positioning method and apparatus. The positioning method includes acquiring a plurality of positioning results including positions of key points of a facial area included in an input image, respectively using a plurality of predetermined positioning models, evaluating the plurality of positioning results using an evaluation model of the positions of the key points, and updating at least one of the plurality of predetermined positioning models and the evaluation model based on a positioning result that is selected, based on a result of the evaluating, from among the plurality of positioning results.

Abstract: A user interface method and apparatus are provided. A user interface method of a smart device includes receiving an electrical signal from an electromyography (EMG) sensor worn on a user, determining a user input based on the received electrical signal and position information about a determined position of a detected touch of the user on a touch screen, and controlling operation of the smart device in response to the determined user input.

Abstract: A method and apparatus for authenticating a user are provided. An authentication apparatus includes a data set generator configured to generate an authentication data set by extracting waveforms from a biosignal of a user, a similarity calculator configured to match each of the extracted waveforms to registered waveforms included in a registration data set, and calculate a similarity between each of the extracted waveforms and the registered waveforms, and an auxiliary similarity calculator configured to extract a representative authentication waveform indicating a representative waveform of the extracted waveforms and a representative registration waveform indicating a representative waveform of the registered waveforms, and calculate a similarity between the representative authentication waveform and the representative registration waveform.

Abstract: Disclosed are an electrocardiogram (ECG) authentication method and apparatus, and a training method and apparatus for training a neural network model used for ECG authentication, the ECG authentication apparatus being configured to acquire an ECG signal of a subject, extract a semantic feature of the ECG signal, and authenticate the subject based on the extracted semantic feature.

Abstract: A face tracking apparatus includes: a face region detector; a segmentation unit; an occlusion probability calculator; and a tracking unit. The face region detector is configured to detect a face region based on an input image. The segmentation unit is configured to segment the face region into a plurality of sub-regions. The occlusion probability calculator configured to calculate occlusion probabilities for the plurality of sub-regions. The tracking unit is configured to track a face included in the input image based on the occlusion probabilities.

Abstract: Provided are a positioning method and apparatus. The positioning method includes acquiring a plurality of positioning results including positions of key points of a facial area included in an input image, respectively using a plurality of predetermined positioning models, evaluating the plurality of positioning results using an evaluation model of the positions of the key points, and updating at least one of the plurality of predetermined positioning models and the evaluation model based on a positioning result that is selected, based on a result of the evaluating, from among the plurality of positioning results.

Abstract: A user interface method and apparatus are provided. A user interface method of a smart device includes receiving an electrical signal from an electromyography (EMG) sensor worn on a user, determining a user input based on the received electrical signal and position information about a determined position of a detected touch of the user on a touch screen, and controlling operation of the smart device in response to the determined user input.

Abstract: Provided are electrocardiogram (ECG)-based authentication and training. An authentication method includes generating a feature vector of an ECG obtained from an entity or a person based on a dictionary, classifying the ECG through a classifier based on the feature vector, and performing authentication based on a classification result.