Abstract: The disclosure relates to KRASG12D inhibitor compounds having the structure of Formula (A) or Formula (B), pharmaceutical compositions thereof, and methods of use thereof for inhibiting, treating, and/or preventing KRASG12D mutation-associated diseases, disorders and conditions.

Abstract: An image processing apparatus and method may accurately separate only humans among moving objects, and also accurately separate even humans who have no motion via human segmentation using a depth data and face detection technology. The apparatus includes a face detecting unit to detect a human face in an input color image, a background model producing/updating unit to produce a background model using a depth data of an input first frame and face detection results, a candidate region extracting unit to produce a candidate region as a human body region by comparing the background model with a depth data of an input second or subsequent frame, and to extract a final candidate region by removing a region containing a moving object other than a human from the candidate region, and a human body region extracting unit to extract the human body region from the candidate region.

Abstract: Disclosed is a 3D face capturing apparatus, method and computer-readable medium. As an example, the 3D face capturing method includes obtaining a face color image, obtaining a face depth image, aligning, by a computer, the face color image and the face depth image, obtaining, by the computer, a 3D face model by 2D modeling of the face color image and covering a modeled 2D face area on an image output by an image alignment module, removing by the computer, depth noise of the 3D face model, and obtaining, by the computer, an accurate 3D face model by aligning the 3D face model and a 3D face template, and removing residual noise based on a registration between the 3D face model and the 3D face template.

Abstract: A multi-view face recognition method and system are provided. In the multi-view face recognition method, two images to be recognized are input, a linear projection matrix is calculated based on grouped images in a training set, two feature vectors corresponding to the two input images are extracted based on the linear projection matrix, a distance between the two extracted feature vectors is calculated, and it is determined based on the distance between the two feature vectors whether the two input images belong to a same person.

Abstract: Disclosed is a 3D face capturing apparatus, method and computer-readable medium. As an example, the 3D face capturing method includes obtaining a face color image, obtaining a face depth image, aligning, by a computer, the face color image and the face depth image, obtaining, by the computer, a 3D face model by 2D modeling of the face color image and covering a modeled 2D face area on an image output by an image alignment module, removing by the computer, depth noise of the 3D face model, and obtaining, by the computer, an accurate 3D face model by aligning the 3D face model and a 3D face template, and removing residual noise based on a registration between the 3D face model and the 3D face template.

Abstract: A multi-view face recognition method and system are provided. In the multi-view face recognition method, two images to be recognized are input, a linear projection matrix is calculated based on grouped images in a training set, two feature vectors corresponding to the two input images are extracted based on the linear projection matrix, a distance between the two extracted feature vectors is calculated, and it is determined based on the distance between the two feature vectors whether the two input images belong to a same person.

Abstract: A method, medium, and apparatus with a generated object descriptor using a curvature gabor filter, with complementary object recognition being performed by applying a general gabor filter and a curvature gabor filter having various curvatures, such that the dimension and efficiency of a feature vector can be increased by detecting correlations between features of an object searching for a parameter and its position of an optimal curvature gabor filter through boosting learning, and projecting the extracted features onto a base vector having the highest classification rate.

Abstract: A face descriptor generating method and apparatus and face recognition method and apparatus using extended local binary pattern (LBP) are provided. Since LBP features are selected by performing a supervised learning process on the extended LBP features and the selected extended LBP features are used in face recognition, it is possible to reduce errors in face recognition or identity verification and to increase face recognition efficiency. In addition, the extended LBP features are used so that it is possible to overcome the problem of time-consumption of the process.

Abstract: A face recognition method and apparatus using extended Gabor wavelet features are provided. In the face recognition method, extended Gabor wavelet features are extracted from a face image by applying an extended Gabor wavelet filter, a Gabor wavelet feature set is selected by performing a supervised learning process on the extended Gabor wavelet features, and the selected Gabor wavelet feature set is used for face recognition. Accordingly, it is possible to solve problems of a high error rate of face recognition and low face recognition efficiency caused from a limitation of parameters of the Gabor wavelet filter. In addition, it is possible to solve the problem of increased calculation complexity caused from using an extended Gabor wavelet filter and to implement robust face recognition which is excellent in dealing with a change in expression and illumination.

Abstract: A method and an apparatus for constructing classifiers based on face texture information and a method and an apparatus for recognizing a face using statistical features of texture information.