Development of a facial image processing algorithm with its application into emotional recognition
碩士 === 長庚大學 === 電子工程學系 === 99 === Abstract Facial expression recognition has become a popular subject in because it is a non-verbal communication between computer and human reaction. We propose a two stage recognition algorithm. It separated into three parts, pre-processing, screening for first...
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ndltd-TW-099CGU054280722015-10-13T20:27:50Z http://ndltd.ncl.edu.tw/handle/26439000077687682089 Development of a facial image processing algorithm with its application into emotional recognition 一個以臉部影像為基礎之情緒辨識演算法開發 Yun Yao Wang 王韻堯 碩士 長庚大學 電子工程學系 99 Abstract Facial expression recognition has become a popular subject in because it is a non-verbal communication between computer and human reaction. We propose a two stage recognition algorithm. It separated into three parts, pre-processing, screening for first stage, and recognition for second stage, respectively. We use a real time object detection algorithm to extract the facial image in pre-processing. In screening part, we calculate the vectors of the images and compare with database by using Long Haar-like filters. And the last part, we extract the information from mouth for positive emotion and eyebrow for negative emotion. Finally, we use Linear Discriminant Function (LDF) to recognize the emotion by using these information. The final percentage of recognition that happy and sad are 86.21%, and angry is 75.86%. S. W. Chen 陳思文 2011 學位論文 ; thesis 73 |
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碩士 === 長庚大學 === 電子工程學系 === 99 === Abstract
Facial expression recognition has become a popular subject in because it is a non-verbal communication between computer and human reaction. We propose a two stage recognition algorithm. It separated into three parts, pre-processing, screening for first stage, and recognition for second stage, respectively. We use a real time object detection algorithm to extract the facial image in pre-processing. In screening part, we calculate the vectors of the images and compare with database by using Long Haar-like filters. And the last part, we extract the information from mouth for positive emotion and eyebrow for negative emotion. Finally, we use Linear Discriminant Function (LDF) to recognize the emotion by using these information. The final percentage of recognition that happy and sad are 86.21%, and angry is 75.86%.
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S. W. Chen |
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S. W. Chen Yun Yao Wang 王韻堯 |
author |
Yun Yao Wang 王韻堯 |
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Yun Yao Wang 王韻堯 Development of a facial image processing algorithm with its application into emotional recognition |
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Yun Yao Wang |
title |
Development of a facial image processing algorithm with its application into emotional recognition |
title_short |
Development of a facial image processing algorithm with its application into emotional recognition |
title_full |
Development of a facial image processing algorithm with its application into emotional recognition |
title_fullStr |
Development of a facial image processing algorithm with its application into emotional recognition |
title_full_unstemmed |
Development of a facial image processing algorithm with its application into emotional recognition |
title_sort |
development of a facial image processing algorithm with its application into emotional recognition |
publishDate |
2011 |
url |
http://ndltd.ncl.edu.tw/handle/26439000077687682089 |
work_keys_str_mv |
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