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基于分割集成的行人检测方法*

DOI: 10.16451/j.cnki.issn1003-6059.201506011, PP. 558-567

Keywords: 行人检测,集成学习,分割集成,方向梯度直方图(HOG)

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Abstract:

为提高行人检测的准确率,提出基于分割集成的方法用于静态图片中的行人检测.先将每个训练样本均匀分割成若干区域,提取特征后利用AdaBoost算法对每个区域建立一个局部分类器,这些局部分类器加权组成一个全局分类器.采用不同的分割方法重复上述过程,得到多个全局分类器.为进一步提高检测效果,得到更好的平均性能,对每种分割方法分别使用方向梯度直方图、多尺度方向梯度直方图特征建立2个全局分类器.当检测新的窗口时,集成上述全局分类器,通过加权投票的方式决定最终的检测结果.在INRIA公共测试集上的实验表明,文中方法有效提高检测效果.

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