| 新生儿疼痛面部表情的特征提取 |
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| 引用本文： | 卢官明,邹婵洁,李晓南,李海波,郭旻. 新生儿疼痛面部表情的特征提取[J]. 南京邮电大学学报(自然科学版), 2008, 28(5) |
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| 作者姓名： | 卢官明 邹婵洁 李晓南 李海波 郭旻 |
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| 作者单位： | 南京邮电大学,通信与信息工程学院,江苏,南京,210003;南京医科大学附属南京儿童医院,江苏,南京,210008;瑞典于默奥大学,应用物理与电子系,S-901 |
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| 基金项目： | Asian-Swedish Research Links Programme，江苏省南京市人事局留学回国人员科技活动择优项目，南京市卫生局医学科技发展重点项目，南京邮电大学校科研基金 |
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| 摘 要： | 针对新生儿的疼痛表情识别,提出了将Gobor小渡变换与改进的KDA相结合的特征提取方法.首先时新生儿面部图像进行Gabor变换,然后针对变换后的Gabor特征,用一种改进的核鉴别分析方法对它进行二次特征提取.该方法从根本上解决了表情识别中因小样本问题而引起的核类内离散度矩阵(kernel within-class scatter matrix)奇异性的问题.最后,对提取的特征用支持向量机进行了疼痛表情的分类识别.实验结果表明,此表情特征提取方法能够显著改善表情识别系统的性能.
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| 关 键 词： | 新生儿疼痛 面部表情 特征提取 Gabor小波变换 核鉴别分析 |
Feature Extraction for Neonatal Facial Expressions of Pain |
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| LU Guan-ming,ZOU Chan-jie,LI Xiao-nan,LI Hai-bo,GUO Min. Feature Extraction for Neonatal Facial Expressions of Pain[J]. JJournal of Nanjing University of Posts and Telecommunications, 2008, 28(5) |
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| Authors: | LU Guan-ming ZOU Chan-jie LI Xiao-nan LI Hai-bo GUO Min |
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| Abstract: | In this paper,we propose a facial expression feature extraction method which combines Gabor wavelet transformation with improved KDA in order to recognize the neonatal facial expression of pain.At first,the neonatal facial image is transformed by Gabor wavelet.Then,the Gabor features are extracted with an improved kernel discriminant analysis method in order to solve the singularity problem of kernel within-class scatter matrix which is caused by the small sample size problem of expression recognition.Based... |
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| Keywords: | neonatal pain facial expression feature extraction Gabor wavelet transform kernel discriminant analysis |
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