Title
Passive and Active Sample Selection and Variance Discriminant Analysis: For Samplebased Face Detection,Used
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Among the many existing categories of face de tection algorithms, the samplebased method is one of the most widelyused approaches. The essence of the samplebased method is to solve a twoclass classification problem of face versus nonface. Many classification algorithms such as the Naive Bayesian, Neural Network and Support Vector Machines (SVM) have been used for this purpose. This thesis showcases a research study into face detection technologies. It has two main parts. Firstly, in the sample preparation section, new passive sample selection and active sample generation algorithms are proposed to assist existing samplebased algorithms in solving the problem of face detection. Secondly, in the classification section, a new Bayesianbased classification method is proposed for face detection.
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