计算机科学 ›› 2011, Vol. 38 ›› Issue (4): 254-256.
• 人工智能 • 上一篇 下一篇
何彦斌,杨志义,马荟,王海鹏,於志文
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基金资助:
HE Yan-bin,YANG Zhi-yi,MA Hui,WANG Hai-peng,YU Zhi-wen
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摘要： 隐马尔科夫模型作为一种统计分析模型，能够通过观测向量序列计算其隐含状态的概率分布密度。提出一种智能空间中基于HMM的场景识别方法，该方法指定系统相关情境信息，确定隐含场景集和观察情境集，采用部分相关情境信息而非全部情境信息作为场景特征参与场景识别，利用HMM对隐含场景间的关系进行建模，设计了基于HMM的场景识别算法。实验结果表明，采用基于HMM的场景识别方法能够获得较高的识别效率。
关键词: 隐马尔科夫模型，场景识别，智能空间
Abstract: Hidden Markov Model, as a statistical model, can get the probability of hidden status by calculating the sequcnce of observed status. In this paper, a recognition approach based on HMM was proposed to infer situation in smart space. The approach infers situation by calculating partly contexts of system-related, using HMM to model the hidden situations. We designed the recognition algorithm based on HMM. Our experimental results show that this method can make a good performs and get a higher efficiency.
Key words: Hidden markov model,Situation recognition,Smart space
何彦斌,杨志义,马荟,王海鹏,於志文. 一种基于HMM的场景识别方法[J]. 计算机科学, 2011, 38(4): 254-256. https://doi.org/
HE Yan-bin,YANG Zhi-yi,MA Hui,WANG Hai-peng,YU Zhi-wen. Method of Situation Recognition Based on Hidden Markov Model[J]. Computer Science, 2011, 38(4): 254-256. https://doi.org/
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