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基于自适应高斯核支持向量机的室内人体存在检测*

, PP. 492-498

Keywords: 多尺度小波,边缘检测,自适应,支持向量机(SVM)

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Abstract:

服务监控对象人体存在检测是室内移动机器人应用中定位、识别与跟踪人的基础,但室内环境的复杂多变性与视觉系统的移动给人体检测带来很大的困难,使得人体检测结果不稳定且有效性差,为此,本文提出一种基于室内移动机器人视觉系统的人体存在检测方法.首先采用多尺度小波变换检测法与边缘连接算子相结合的方法提取图片边缘特征,并提出一种形态学方法去除非目标小区域、不封闭的边缘线或孤立点,利用边缘图片的不变Hu矩作为模式识别特征向量.然后应用自适应高斯核函数软间隔支持向量机建立两类识别分类器,并与基于不同特征建立分类器的人体存在检测法和基于不同分类方法建立分类器的人体存在检测法进行分析比较,结果表明本文算法是更稳定有效的.

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