National Changhua University of Education Institutional Repository : Item 987654321/11788
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 6507/11669
造访人次 : 29943548      在线人数 : 432
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 进阶搜寻

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.ncue.edu.tw/ir/handle/987654321/11788

题名: An Interaction-Embedded HMM Framework for Human Behavior Understanding: with Nursing Environments as Examples
作者: Liu, Chin-De;Chung, Yi-Nung;Chung, Pau-Choo
贡献者: 電機工程學系
日期: 2010-09
上传时间: 2012-07-02T02:08:41Z
出版者: IEEE
摘要: This paper presents an interaction-embedded hidden Markov model (IE-HMM) framework for automatically detecting and classifying individual human behaviors and group interactions. The proposed framework comprises a switch control (SC) module, an individual duration HMM (IDHMM) module, and an interaction-coupled duration HMM (ICDHMM) module. By analyzing the relative distances between the various participants in each scene, and monitoring the duration for which these distances are maintained, the SC module assigns each participant to an individual behavior unit (comprising a single participant) or an interaction behavior unit (comprising two or more participants). The individual behavior units are passed to the IDHMM module, which classifies the corresponding human behavior in accordance with the pose, motion, and duration information using duration HMM (DHMM). Similarly, the interaction behavior units are dispatched to the ICDHMM module, where the corresponding interaction mode is classified using an integrated scheme comprising multiple coupled-duration HMM (CDHMM), in which each state has an embedded coupled HMM (CHMM). The validity of the IE-HMM framework is confirmed by analyzing the human actions and interactions observed in a nursing home environment. The results confirm that the atomic behavior unit concept embedded in the SC module enables the IE-HMM framework to recognize multiple concurrent actions and interactions within a single scene. Overall, it is shown that the proposed framework has a recognition performance of 100% when applied to the analysis of individual human actions and 95% when applied to that of group interactions.
關聯: IEEE Trans.on Information Technology in Biomedicine, 14(5): 1236-1246
显示于类别:[電機工程學系] 期刊論文

文件中的档案:

档案 大小格式浏览次数
index.html0KbHTML686检视/开启


在NCUEIR中所有的数据项都受到原著作权保护.

 


DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈