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联合特征在行人检测中的应用

DOI: 10.11834/jig.20120510

Keywords: 行人检测,二阶梯度光流法,运动特征,支持向量机,均值漂移

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Abstract:

提出一种基于动态和静态联合特征的行人检测方法,用于运动背景下的行人检测。运动背景的检测难度在于背景与目标的分离,该方法采用一种改进的Nagel二阶梯度光流算法生成图像的光流场,从中提取行人运动特征(MBH)和IMH(internalmotionhistograms),增强特征重复性以提高鉴别能力。实验中使用Libsvm训练线性SVM(supportvectormachine)分类器,使用MeanShift算法优化分类结果。实验在1093组图像上获得98%的识别率,证明该方法可以在运动背景下的图像序列上获得较出色的检测效果。

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