基于多核学习SVM的图像分类识别算法An image classification and recognition algorithm based on multi-kernel learning SVM
李红丽,许春香,马耀锋
摘要(Abstract)：
针对单核支持向量机在图像分类识别中检测精度较低的问题,提出一种多核学习SVM的图像分类识别算法,并将其应用到行人检测问题中。首先,提取行人的积分通道特征包括梯度直方图、彩色通道和梯度特征;然后,使用直方图交叉核、多项式核和径向基核构建混合核SVM分类器;最后,使用交叉验证和网格搜索的方法确定各种核的融合系数。在TUD数据集上的测试结果表明,该方法具有较好的鲁棒性和较高的检测精度。
关键词(KeyWords)： 支持向量机;多核学习;行人检测;图像识别;直方图交叉核;交叉验证
基金项目(Foundation): 河南省科技厅科技攻关项目(172102210604;162102210131);; 河南省高等学校重点研究项目(16B510008);; 中州大学科技创新团队建设计划项目(CXTD2017K4);; 郑州工程技术学院教育教学改革研究项目(16)~~
作者(Author): 李红丽,许春香,马耀锋
DOI: 10.16652/j.issn.1004-373x.2018.06.012
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