摘要
为了更好地在日常生活中给人提供智能化服务,对家庭环境下人的行为理解问题进行了研究.首先利用运动目标检测方法提取运动人体在环境中的坐标,然后结合行为特点把场景划分成不同区域,建立人体在环境中的位置关联矩阵和时空关联矩阵.通过马尔可夫模型统计出人体在空间中的位置状态转移概率矩阵及其状态持续时间矩阵,生成日常行为模板.根据当前行为与日常行为模板的相似度可检测出反常习惯和突发异常行为,同时可根据不同区域的行为模式分析人的意图.在智能空间平台下利用机器视觉技术基于场景信息实现了人的行为理解,并通过实验表明了方法的有效性.
Challenges in understanding human behavior in a home environment were studied in order to provide more intelligent services.First,spatial coordinates of human bodies were extracted from motion detector data.Then,by dividing the environment into different stations and observing the types of behavior typical at various periods of time in that area,a station-based occupational matrix with a time dimension was established.After establishing the station state transitional probability matrix and the state duration time distribution matrix based on the Markov model,a daily behavioral template was constructed.Behavior outside of normal habits as well as behavior resulting from unexpected accidents could be detected in real-time by comparing the similarity of current behavior with templates showing typical daily behavior.At the same time,human intention could be predicted based on behavior patterns typical in different areas.In this way,better understanding of human behavior becomes possible.The effectiveness of this method was proved by experiments.
出处
《智能系统学报》
2010年第1期57-62,共6页
CAAI Transactions on Intelligent Systems
基金
国家高技术研究发展计划重点资助项目(2006AA040206)
关键词
智能空间
机器视觉
场景信息
行为理解
异常检测
意图识别
intelligent space
machine vision
scene knowledge
behavioral understanding
anomaly detection
intention recognition
