| 一种基于布尔核SVM的人脸识别策略 |
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| 引用本文： | 任天成,刘新,崔克彬.一种基于布尔核SVM的人脸识别策略[J].山东电力技术,2011(5):58-62. |
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| 作者姓名： | 任天成 刘新 崔克彬 |
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| 作者单位： | [1]山东电力研究院．山东济南250002 [2]华北电力大学,北京071003 |
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| 摘 要： | 针对人脸识别问题,给出基于布尔核的SVM识别策略,该策略首先应用K-L变换对人脸图像进行特征参数的提取,然后将提取出的特征进行0-1化处理,用于构造基于布尔核的SVM。在标准人脸库ORL上的试验结果表明,基于布尔核函数的SVM在分类准确率上明显高于传统PCA算法,同时,也优于线性SVM。
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| 关 键 词： | 人脸识别 K-L变换 支持向量机 布尔核函数 多分类 |
A Recognizing Strategy for the Problem of Face Based on Boolean Kernel Function SVM |
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| Abstract: | For the problem of face recognition, a recognizing strategy based on Boolean kernel function SVM is proposed. Firstly, Karhunen-Loeve transform is employed to get the representation basis of face image set ; secondly, the extracted characteristics is translated into 0-1 format; thirdly, SVM based Boolean kernel function are used to classify. The face recognition experiment with ORL face databases shows that the proposed method led to significantly better classification accuracy compared with traditional PCA method and Linear SVM. |
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| Keywords: | face recognition support vector machines Karhunen-Loeve transform Boolean kernel function multi-classification |
| 本文献已被 CNKI 维普 等数据库收录！ |
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