Passive and Active Sample Selection and Variance Discriminant Analysis (Paperback)

Among the many existing categories of face de- tection algorithms, the sample-based method is one of the most widely-used approaches. The essence of the sample-based method is to solve a two-class classification problem of face versus non-face. 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 sample-based algorithms in solving the problem of face detection. Secondly, in the classification section, a new Bayesian-based classification method is proposed for face detection.

General

Imprint:	Lap Lambert Academic Publishing
Country of origin:	Germany
Release date:	May 2011
First published:	May 2011
Authors:	Yu Wei
Dimensions:	229 x 152 x 10mm (L x W x T)
Format:	Paperback - Trade
Pages:	168
ISBN-13:	978-3-8443-9274-6
Categories:	Books > Computing & IT > General theory of computing > General
LSN:	3-8443-9274-2
Barcode:	9783844392746

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