| 摘要 |
A face recognition apparatus and method using Principal Component Analysis (PCA) learning per subgroup, the face recognition apparatus includes: a learning unit which performs Principal Component Analysis (PCA) learning on each of a plurality of subgroups constituting a training data set, and then performs Linear Discriminant Analysis (LDA) learning on the training data set, thereby generating a PCA-based LDA (PCLDA) basis vector set of each subgroup; a feature vector extraction unit which projects a PCLDA basis vector set of each subgroup to an input image and extracts a feature vector set of the input image with respect to each subgroup; a feature vector storing unit which projects a PCLDA basis vector set of each subgroup to each of a plurality of face images to be registered, thereby generating a feature vector set of each registered image with respect to each subgroup, and storing the feature vector set in a database; and a similarity calculation unit which calculates a similarity between the input image and each registered image.
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