| 基于支持向量机的新生儿疼痛表情识别 |
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| 引用本文： | 高众,卢官明.基于支持向量机的新生儿疼痛表情识别[J].重庆科技学院学报(自然科学版),2009,11(2). |
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| 作者姓名： | 高众 卢官明 |
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| 作者单位： | 南京邮电大学,南京,210003 |
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| 基金项目： | 江苏省高校自然科学基金 |
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| 摘 要： | 研究不同的特征提取方法和分类方法在分类问题上的性能,其中包括主分量分析(PCA)、Adaboost算法、支持向量机(SVM),并进行了仿真实验.仿真结果表明,相对于使用主分量分析方法,利用Adaboost算法结合支持向量机的分类方法进行特征提取和选择的效果更好.
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| 关 键 词： | 表情识别 主分量分析 Adaboost算法 支持向量机 |
Recognition of Neonatal Facial Expressions of Acute Pain Based on Support Vector Machine |
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| GAO Zhong,LU Guan-ming.Recognition of Neonatal Facial Expressions of Acute Pain Based on Support Vector Machine[J].Journal of Chongqing University of Science and Technology:Natural Science Edition,2009,11(2). |
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| Authors: | GAO Zhong LU Guan-ming |
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| Affiliation: | Nanjing University of Posts and Telecommunications;Nanjing 210003 |
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| Abstract: | In this paper,feature extraction,feature selection and expression classification are mainly studied.These algorithms include PCA,Adaboost and Support Vector Machine.The experimental results show that using Adaboost algorithm to extract and select features has better performance in expression classification based on Support Vector Machine. |
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| Keywords: | facial expressions recognition PCA Adaboost algorithm support vector machine |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
