Passive and Active Sample Selection and Variance Discriminant Analysis - For Sample-based Face Detection

by Wei, Yu
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Wei, Yu Passive and Active Sample Selection and Variance Discriminant Analysis - For Sample-based Face Detection
Wei, Yu - Passive and Active Sample Selection and Variance Discriminant Analysis - For Sample-based Face Detection

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Description

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.

Contributors

Author:
Wei, Yu

Further information

Biography Artist:
Dr. Yu Wei is a software engineer in Semiconductor Technologies & Instruments, Singapore. He is an expert in machine vision, pattern recognition and image processing. He obtained his B.Sc. from Zhejiang University in China in 1993, and Ph.D. from NTU in 2009. He now resides in Singapore.
Language:
Englisch
Number of Pages:
168
Media Type:
Taschenbuch
Publisher:
Dictus Publishing

Master Data

Product Type:
Paperback book
Release date:
20 May 2011
Package Dimensions:
0.22 x 0.15 x 0.01 m; 0.299 kg
GTIN:
09783844392746
DUIN:
16ADLKBF4GP
£59.99
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