Detection of the side faces of the image (part two)

As the appearance of a person had always been the primary identity, many had researched and introduced different ways to identify people. That includes fingerprint identification and handprint identification. Face detection is one of the ways to identify a human face in images. It had since impro...

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Main Author: Wu, Xingzhi.
Other Authors: Sung, Eric
Format: Final Year Project
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/46221
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-462212023-07-07T15:49:37Z Detection of the side faces of the image (part two) Wu, Xingzhi. Sung, Eric School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Biometrics As the appearance of a person had always been the primary identity, many had researched and introduced different ways to identify people. That includes fingerprint identification and handprint identification. Face detection is one of the ways to identify a human face in images. It had since improved and used in multiple applications such as person identification and surveillance. Though the side face detection have not been able to live up to the expectation, it will be beneficial to implement side face detection on applications for criminal identification and image annotation. This project focuses on using the Viola-Jones method to detect side-view faces and analyses the results that will be obtain. The algorithm uses the Haar-basis functions to get features to be learned in the AdaBoost learning algorithm. It is implemented for the selection of features. The features then will be used to go through classifiers. C++ Computing language and OpenCV is chosen as the platform to analyze the side face detection. Bachelor of Engineering 2011-07-08T01:05:14Z 2011-07-08T01:05:14Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/46221 en Nanyang Technological University 50 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Biometrics
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Biometrics
Wu, Xingzhi.
Detection of the side faces of the image (part two)
description As the appearance of a person had always been the primary identity, many had researched and introduced different ways to identify people. That includes fingerprint identification and handprint identification. Face detection is one of the ways to identify a human face in images. It had since improved and used in multiple applications such as person identification and surveillance. Though the side face detection have not been able to live up to the expectation, it will be beneficial to implement side face detection on applications for criminal identification and image annotation. This project focuses on using the Viola-Jones method to detect side-view faces and analyses the results that will be obtain. The algorithm uses the Haar-basis functions to get features to be learned in the AdaBoost learning algorithm. It is implemented for the selection of features. The features then will be used to go through classifiers. C++ Computing language and OpenCV is chosen as the platform to analyze the side face detection.
author2 Sung, Eric
author_facet Sung, Eric
Wu, Xingzhi.
format Final Year Project
author Wu, Xingzhi.
author_sort Wu, Xingzhi.
title Detection of the side faces of the image (part two)
title_short Detection of the side faces of the image (part two)
title_full Detection of the side faces of the image (part two)
title_fullStr Detection of the side faces of the image (part two)
title_full_unstemmed Detection of the side faces of the image (part two)
title_sort detection of the side faces of the image (part two)
publishDate 2011
url http://hdl.handle.net/10356/46221
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