Abstract:
A medical image registration method includes performing a first registration by registering first medical images, including a registration image and a display image, the display image being an image to be displayed, performing a second registration by registering a second medical image having a different modality than a modality of the first medical images, with the registration image, and extracting a cross-section of one of the first medical images, corresponding to a cross-section of the second medical image, from the display image, according to the first registration and the second registration.
Abstract:
A method and an apparatus for recognizing an object are disclosed. The apparatus may extract a plurality of features from an input image using a single recognition model and recognize an object in the input image based on the extracted features. The single recognition model may include at least one compression layer configured to compress input information and at least one decompression layer configured to decompress the compressed information to determine the features.
Abstract:
A method and an apparatus for recognizing an object are disclosed. The apparatus may extract a plurality of features from an input image using a single recognition model and recognize an object in the input image based on the extracted features. The single recognition model may include at least one compression layer configured to compress input information and at least one decompression layer configured to decompress the compressed information to determine the features.
Abstract:
An adaptive updating method of an enrollment database is disclosed. The method may include extracting a first feature vector from an input image of a user, determining whether the input image is to be enrolled in an enrollment database based on the first feature vector, second feature vectors of enrollment images including initial enrollment images enrolled in the enrollment database, and a representative vector representing the initial enrollment images, and enrolling the input image in the enrollment database based on a result of the determining.
Abstract:
A method of segmenting an object from an image includes receiving an input image including an object; generating an output image corresponding to the object from the input image using an image model; and extracting an object image from the output image.
Abstract:
A method of generating a three-dimensional (3D) face model includes extracting feature points of a face from input images comprising a first face image and a second face image; deforming a generic 3D face model to a personalized 3D face model based on the feature points; projecting the personalized 3D face model to each of the first face image and the second face image; and refining the personalized 3D face model based on a difference in texture patterns between the first face image to which the personalized 3D face model is projected and the second face image to which the personalized 3D face model is projected.
Abstract:
A method of segmenting an object from an image includes receiving an input image including an object; generating an output image corresponding to the object from the input image using an image model; and extracting an object image from the output image.
Abstract:
A liveness test method and apparatus is disclosed. A processor implemented liveness test method includes extracting an interest region of an object from a portion of the object in an input image, performing a liveness test on the object using a neural network model-based liveness test model, the liveness test model using image information of the interest region as provided first input image information to the liveness test model and determining liveness based at least on extracted texture information from the information of the interest region by the liveness test model, and indicating a result of the liveness test.
Abstract:
A method of adaptively updating an enrollment database is disclosed. The method may include extracting a first feature vector from an input image, the input image including a face of a user, determining whether to enroll the input image in the enrollment database based on the first feature vector, second feature vectors of enrollment images and a representative vector, the second feature vectors of the enrollment images being enrolled in the enrollment database, and the representative vector representing the second feature vectors, and enrolling the input image in the enrollment database based on a result of the determining.
Abstract:
A medical image registration method and apparatus are described. By performance of a medical image registration method, a highly accurate registered image, in which breathing deformation information is considered, may be obtained by generation of non-real-time medical images in which the breathing deformation information is reflected before a medical procedure is conducted and by rigid registration of a real-time medical image and the generated non-real-time medical images during the medical procedure.