家庭智能空间下基于HMM的人轨迹分析方法  

Human Trajectory Analysis Method Based on Hidden Markov Model in Home Intelligent Space

作　　者：赵扬[1] 田国会[1] 尹建芹[2] 樊建霞[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061 [2]济南大学信息科学与工程学院,济南250022

出　　处：《模式识别与人工智能》2015年第6期542-549,共8页Pattern Recognition and Artificial Intelligence

基　　金：国家863计划项目(No.2009AA04Z220);国家自然科学基金项目(No.61203341);山东省自然科学基金项目(No.ZR2011FM011);山东省高等学校科技发展计划项目(No.J11LG01)资助

摘　　要：对人行为的感知和预推理是家庭智能空间技术的关键环节.文中提出一种基于隐马尔可夫模型(HMM)的人轨迹分析方法.该方法首先将平面空间离散化为"瓷砖格",离线对各预设轨迹建立HMM模型.然后针对在线分析,提出一种类似滑动窗口的轨迹分割方案,该方案能实时有效地分割轨迹段,并适时激发轨迹匹配进程.最后智能空间依据匹配结果做出轨迹预测.实验表明,文中方法能有效预测人的轨迹,且满足实时性要求,有助于智能空间更好进行决策.Recognition and pre-reasoning of human activity is essential in home intelligent space. In this paper, an approach based on hidden markov model （ HMM） is proposed for human trajectory analysis. Firstly, the plan is discretized into tile blocks, and HMM models for human trajectories are set up off-line. Then, aiming at the online analysis, a sliding-window-like approach is put forward to achieve real-time trajectory segmentation and activate model matching process intelligently. Finally, a predicition of human trajectory is made by the intelligent space according to matching results. Experimental results show that the proposed approach achieves good performance in real-time trajectory analysis. Furthermore, the proposed approach can help home intelligent space make wiser decision.

关 键 词：智能空间 隐马尔可夫模型( HMM) 行为识别 轨迹分割 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] O211.62[自动化与计算机技术—控制科学与工程]