A Study for Facial Feature Localization and Extraction

碩士 === 義守大學 === 電子工程學系碩士班 === 98 === This research is mainly to develop a system for face detection and facial feature extraction. The algorithm consists of face detection, mouth detection, skin color detection and eye detection. Firstly, a face image with complex background is extracted to use skin...

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Main Authors: Chin-Yuan Kuo, 郭晉源
Other Authors: Yih-Ming Su
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/06281341685571701743
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spelling ndltd-TW-098ISU054280232015-10-13T18:25:52Z http://ndltd.ncl.edu.tw/handle/06281341685571701743 A Study for Facial Feature Localization and Extraction 臉部特徵定位與擷取之研究 Chin-Yuan Kuo 郭晉源 碩士 義守大學 電子工程學系碩士班 98 This research is mainly to develop a system for face detection and facial feature extraction. The algorithm consists of face detection, mouth detection, skin color detection and eye detection. Firstly, a face image with complex background is extracted to use skin color detection and remove the background. Then, rectangle feature extraction and AdaBoost classification approaches are used to localize the face region. Furthermore, the eye and lip candidate region are divided using facial geometrize relationship. In the eye candidate region, a template matching approach is used to obtain the position, and then the range of the lip candidate region is narrowed to achieve better result. The best lip region is extracted using edge projection and color difference between the lip and skin color after detecting lip candidate region. The result shows that the use of skin color detection can not only reduce the computation time for face detection, but also have high level of fault tolerant in the complex environment. The experiment results used self-made videos to do the test of facial feature position and selection. The system performed 15 frames/s, and also achieved the overall detection rate of 75 %. Yih-Ming Su 蘇義明 2010 學位論文 ; thesis 55 zh-TW
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description 碩士 === 義守大學 === 電子工程學系碩士班 === 98 === This research is mainly to develop a system for face detection and facial feature extraction. The algorithm consists of face detection, mouth detection, skin color detection and eye detection. Firstly, a face image with complex background is extracted to use skin color detection and remove the background. Then, rectangle feature extraction and AdaBoost classification approaches are used to localize the face region. Furthermore, the eye and lip candidate region are divided using facial geometrize relationship. In the eye candidate region, a template matching approach is used to obtain the position, and then the range of the lip candidate region is narrowed to achieve better result. The best lip region is extracted using edge projection and color difference between the lip and skin color after detecting lip candidate region. The result shows that the use of skin color detection can not only reduce the computation time for face detection, but also have high level of fault tolerant in the complex environment. The experiment results used self-made videos to do the test of facial feature position and selection. The system performed 15 frames/s, and also achieved the overall detection rate of 75 %.
author2 Yih-Ming Su
author_facet Yih-Ming Su
Chin-Yuan Kuo
郭晉源
author Chin-Yuan Kuo
郭晉源
spellingShingle Chin-Yuan Kuo
郭晉源
A Study for Facial Feature Localization and Extraction
author_sort Chin-Yuan Kuo
title A Study for Facial Feature Localization and Extraction
title_short A Study for Facial Feature Localization and Extraction
title_full A Study for Facial Feature Localization and Extraction
title_fullStr A Study for Facial Feature Localization and Extraction
title_full_unstemmed A Study for Facial Feature Localization and Extraction
title_sort study for facial feature localization and extraction
publishDate 2010
url http://ndltd.ncl.edu.tw/handle/06281341685571701743
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