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基于PLS-VIP特征降维的车辆检测

, PP. 98-105

Keywords: 交通工程,智能交通,偏最小二乘法,车辆特征降维,变量投影重要性

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Abstract:

?为了提高车辆视频检测和训练速度,针对车辆视觉特征维数较高的普遍问题,构造了一种特征降维方法,采用偏最小二乘(PLS)法对包含正、负样本的训练集图像进行分解;通过变量投影重要性分析(VIP)法评价原始特征对分解结果的贡献得分,将得分降序排序并选用高分特征直接张成低维空间,实现数据降维,并以低维数据为输入项,学习得到车辆分类器。对于新图像,直接抽取对应的高分特征进行检测,避免了常见的数据投影过程。研究结果表明:采用PLS-VIP降维,车辆图像的聚类性更明显,聚类正确率优于传统的主成分分析法、PLS法、非线性降维的等距映射法、特征脸法以及PLS衍生方法,降维后检测耗时达到降维前的22%。

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