| 基于支持向量机方法的车型分类 |
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| 引用本文： | 葛威,朱光喜,徐海祥,谢磊,陶平安. 基于支持向量机方法的车型分类[J]. 计算机工程与应用, 2006, 42(21): 210-213 |
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| 作者姓名： | 葛威 朱光喜 徐海祥 谢磊 陶平安 |
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| 作者单位： | 华中科技大学电子与信息工程系,武汉,430074;武汉市城市规划设计研究院,武汉,430014 |
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| 摘 要： | 车型分类是交通流检测系统的子功能,也是智能交通系统(ITS)中的重要环节。支持向量机方法被看作是对传统学习分类方法的一个好的替代,特别在小样本、非线性情况下,具有较好的泛化性能。论文基于视频检测技术,采用支持向量机方法对车型分类进行了研究。实验表明,支持向量机方法能获得比神经网络方法更好的车型分类性能。
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| 关 键 词： | 车型分类 统计学习理论 支持向量机 神经网络 |
| 文章编号： | 1002-8331-（2006）21-0210-04 |
| 收稿时间： | 2005-11-01 |
| 修稿时间： | 2005-11-01 |
Vehicle Classification Based on Support Vector Machine |
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| Ge Wei,Zhu Guangxi,Xu Haixiang,Xie Lei,Tao Ping'an. Vehicle Classification Based on Support Vector Machine[J]. Computer Engineering and Applications, 2006, 42(21): 210-213 |
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| Authors: | Ge Wei Zhu Guangxi Xu Haixiang Xie Lei Tao Ping'an |
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| Affiliation: | 1 Department of Electronics and Information Engineering,Huazhong University of Science and Technology, Wuhan 430074; 2 Institute of Wuhan Urban Planning Design,Wuhan 430014 |
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| Abstract: | Vehicle Classification is a sub-function of the vehicle detection system,is also an important part of the intelligence transportation system(ITS).Support Vector Machine approach is considered a good candidate because of its good generalization performance,especially when the number of training samples is very small and input space is nonlinear.This paper presents a study on the vehicle classification based on support vector machine.Experimental results indicate that the classification performance of support vector machine is better than that of neural networks. |
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| Keywords: | vehicle classification statistical learning theory Support Vector Machine Neural Networks |
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