Image analysis – Learning systems – Trainable classifiers or pattern recognizers
Reexamination Certificate
2004-12-03
2010-06-08
Bella, Matthew C (Department: 2624)
Image analysis
Learning systems
Trainable classifiers or pattern recognizers
C382S155000, C382S160000, C382S117000, C382S118000, C382S201000, C382S205000
Reexamination Certificate
active
07734087
ABSTRACT:
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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Hwang Won-jun
Kim Tae-kyun
Bella Matthew C
Newman Michael A
Samsung Electronics Co,. Ltd.
Staas & Halsey , LLP
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