| 郭烈,张明恒,李琳辉,赵一兵.一种基于支持向量机的行人识别方法研究[J].,2011,(4):604-610 |
| 一种基于支持向量机的行人识别方法研究 |
| Research on pedestrian recognition method based on support vector machines |
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| DOI：10.7511/dllgxb201104024 |
| 中文关键词: 汽车主动安全 行人识别 AdaBoost算法 支持向量机 |
| 英文关键词: automotive active safety pedestrian recognition AdaBoost algorithm support vector machines |
| 基金项目:中央高校基本科研业务费资助项目(20083013893308). |
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| 中文摘要: |
| 研究了基于支持向量机的车辆前方行人识别方法．通过提取样本的类Haar特征,采用AdaBoost算法训练得到了分割行人的级联分类器,实现了行人候选区域的快速分割；提取了样本的纹理特征、对称性特征、边界矩特征以及梯度方向特征,组成表征行人的多维特征向量,采用支持向量机训练得到了识别行人的分类器．试验结果验证了所提算法的有效性,获得约75%的行人检测率． |
| 英文摘要: |
| A support vector machine-based recognition method of pedestrian in front of automotive is introduced. The Haar-like characteristics of samples were selected and calculated, and the cascaded classifiers were trained using AdaBoost algorithm to fastly segment candidate pedestrian areas from the image. To form a multidimensional pedestrian describing vector, the texture and symmetry features, as well as boundary moment and gradient oriented features were abstracted from sample images, and the classifiers for pedestrian recognition were realized by support vector machines. Experimental results validate the effects of the proposed method by about 75% of pedestrian detection rate. |
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