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- W149590219 abstract "We present an effective and real-time face detection method based on Principal Component Analysis(PCA) and Support Vector Machines(SVMs). We extract simple Haar-like features from training images that consist of face and non-face images, reinterpret the features with PCA, and select useful ones from the large number of extracted features. With the selected features, we construct a face detector using an SVM appropriate for binary classification. The face detector is not affected by the size of a training data set in a significant way, so that it showed 90.1 % detection rates with a small quantity of training data. it can process 8 frames per second for pixel images. This is an acceptable processing time for a real-time system." @default.
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- W149590219 date "2006-01-01" @default.
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- W149590219 title "Effective Face Detection Using Principle Component Analysis and Support Vector Machine" @default.
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