潘月浩,宋执环,杜往泽,吴乐刚.适用于老年公寓的动作识别设计方法[J].电子测量与仪器学报,2017,31(1):29-35
适用于老年公寓的动作识别设计方法
Design method for action recognition applied to senile apartment
  
DOI:10.13382/j.jemi.2017.01.005
中文关键词:  视频监控  混合高斯背景建模  运动特征  形态特征  HMM
英文关键词:video surveillance  GMM  motion features  morphological features  HMM
基金项目:国家科技型中小企业技术创新项目(14C26213301407)、浙江省科技型中小企业技术创新项目(2014D40014)资助
作者单位
潘月浩 浙江大学控制科学与工程学院杭州310027 
宋执环 浙江大学控制科学与工程学院杭州310027 
杜往泽 浙江大学控制科学与工程学院杭州310027 
吴乐刚 杭州三云科技有限公司杭州310013 
AuthorInstitution
Pan Yuehao College of Industrial Control, Zhejiang University, Hangzhou 310027, China 
Song Zhihuan College of Industrial Control, Zhejiang University, Hangzhou 310027, China 
Du Wangze College of Industrial Control, Zhejiang University, Hangzhou 310027, China 
Wu Legang San Cloud Technology Co. Ltd., Hangzhou 310013, China 
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中文摘要:
      为帮助老年公寓监护人员及时发现老年人摔倒等动作,提出了一种基于视频监控的动作识别方法。对监控视频,首先通过基于HSV空间的混合高斯背景建模方法提取前景图像,然后利用所提出的运动特征和形态特征相结合的方式进行特征提取,最后通过具有高斯输出的HMM模型实现动作类型的识别。提出的方法能够适应光照变化影响,对不同动作的动作方向和动作幅度变化具有很好的鲁棒性,实验中动作的识别准确率达到90%。结果表明,本方法能够满足老年公寓动作识别的基本要求,具有一定的实用价值。
英文摘要:
      To help nursing staff in senile apartment find the elderly fall and other actions timely, an action recognition method based on video surveillance is proposed. Firstly, the foreground images are extracted by the GMM background modeling method in HS color space. Feature extraction is performed by combining the motion features and morphological features. And action recognition can be achieved by HMM with Gaussian output. The method proposed in this paper can adapt to the changes of illumination. The method also has good robustness to the change of motion direction and motion range, and the recognition accuracy rate reaches 90%. The result shows that the method can meet the basic requirements of action recognition and the method has certain practical value.
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