Abstract:
An electronic device is provided. The electronic device includes a first display panel including a first clock generator and that generates a first signal according to the first clock generator in response to a screen update request signal, a second display panel including a second clock generator and that generates a second signal according to the second clock generator in response to a screen update request signal, and a controller that transmits the screen update request signal to the first display panel and the second display panel and that receives the first signal and the second signal and that compares the first signal and the second signal to adjust a clock of at least one of the first clock generator and the second clock generator.
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:
At least one example embodiment discloses a method of extracting a feature of an input image. The method includes constructing an example pyramid including at least one hierarchical level based on stored example images, generating a codebook in each of the at least one hierarchical level, calculating a similarity between the codebook and the input image, and extracting a feature of the input image based on the similarity.
Abstract:
Provided are a method and apparatus for registering medical images. The method includes: setting, as a reference, axis an axis of a probe that is disposed to be parallel to an axis of an object; extracting a first sub-object from a first medical image that is obtained by using the probe; extracting a second sub-object from a second medical image that has a modality different from a modality of the first medical image; and registering the first medical image and the second medical image by aligning the first sub-object and the second sub-object about the reference axis.
Abstract:
A processor of an electronic device according to an embodiment may be configured to identify first graphs included in a first model on the basis of a request for driving the first model, wherein the first model is stored in non-volatile memory of the electronic device. The processor may be configured to identify at least one graph, corresponding to at least one of the first graphs, among second graphs included in one or more second models which are different from the first model and stored in volatile memory. The processor may be configured to obtain, on the basis of the at least one identified graph among the second graphs, an instance for controlling the first model. The processor may be configured to execute a function related to the first model on the basis of the instance.
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 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 three-dimensional (3D) face modeling method and apparatus is disclosed. The 3D face modeling apparatus may generate a personalized 3D face model using a two-dimensional (2D) input image and a generic 3D face model, obtain a depth image and a texture image using the generated personalized 3D face model, determine a patch region of each of the depth image and the texture image, and adjust a shape of the personalized 3D face model based on a matching relationship between the patch region of the depth image and the patch region of the texture image.
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:
An apparatus and corresponding method are provided to match images and include assigning depth candidate values to a pixel in a first image, and reassigning third depth candidate values to a first pixel in the first image based on first depth candidate values assigned to the first pixel and second depth candidate values assigned to a second pixel adjacent to the first pixel. The apparatus and method also include determining one of the third depth candidate values to be a depth value of the first pixel, and matching the first pixel and a third pixel in a second image corresponding to the determined depth value of the first pixel.