期刊文献+

基于全方位视觉的独居老人监护系统 被引量:6

Monitoring System for Elderly People Living Alone Based on Omni-directional Vision
下载PDF
导出
摘要 现有的独居老人监护系统存在算法复杂度高、监护效率低、不能保护老人日常隐私等问题。为此,提出一种基于全方位视觉的独居老人监护系统。利用全方位视觉传感器(ODVS)获取老人的全景视频图像,设计运动历史/能量图像算法用于目标跟踪,根据ODVS的成像特点,采用与ODVS距离位置不同的人体模型实现姿态识别,建立家庭空间与环境要素之间的映射关联,以提高行为检测的鲁棒性和可靠性,并通过ODVS标定和人体对象跟踪获得老人的活动量信息。实验结果表明,该系统的鲁棒性和实时性较强,检测准确率较高,能满足独居老人监护的需要。 Aiming at the problem of high algorithm complexity,low monitoring efficiency and privacy disclosure for existed monitoring system of elderly people living alone,this paper proposes a monitoring system for elderly people living alone based on omni-directional vision.It uses Omni-directional Vision Sensor(ODVS) to get panoramic image,and designs a Motion History or Energy Images(MHoEI) algorithm for the motion object tracking.In the posture recognition,different human model algorithms are applied in accordance with the imaging characteristics of ODVS.For the behavior analysis,a calibrated one-to-one correspondence is adopted between the ground locations and the environmental factors.Both the reliability of behavior detection and the robustness of behavior detection are significant expanded.In addition,elderly activities are accurately obtained by using ODVS calibration and effective tracking for the human object.Experimental results show that this system has high robustness,instantaneity and accuracy rate of the detection.It is adequate to meet current needs by protecting privacy.
出处 《计算机工程》 CAS CSCD 2013年第8期44-49,59,共7页 Computer Engineering
基金 国家自然科学基金资助项目(61070134)
关键词 独居老人 全方位视觉传感器 运动历史 能量图像算法 姿态识别 异常行为分析 全方位视觉传感器标定 elderly people living alone Omni-directional Vision Sensor(ODVS) Motion History or Energy Images(MHoEI) algorithm pose identification abnormal behavior analysis ODVS calibration
  • 相关文献

参考文献14

  • 1汤一平,顾校凯,孙黉杰,王炜.基于活动量分析的独居老人远程监护系统的研究[J].计算机工程与应用,2007,43(3):211-213. 被引量:13
  • 2Back I,Kallio J,Perala S,et al.Remote Monitoring of NursingHome Residents Using a Humanoid Robot[J].Journal of Tele-medicine and Telecare,2012,18(6):357-361.
  • 3Sixsmith A,Johnson N.A Smart Sensor to Detect the Falls ofthe Elderly[J].IEEE Pervasive Computing,2004,3(2):42-47.
  • 4Taylor M E,Ketels M M,Delbaere K,et al.Gait Impairmentand Falls in Cognitively Impaired Older Adults:An Explana-tory Model of Sensorimotor and Neuropsychological Media-tors[J].Age and Ageing,2012,41(5):665-669.
  • 5Kim S H,Kim D W.A Study on Real-time Fall DetectionSystems Using Acceleration Sensor and Tilt Sensor[J].SensorLetters,2012,10(5/6):1302-1307.
  • 6Hynes M,Wang Han,Kilmartin L.Monitoring of ActivityLevels of the Elderly in Home and Community EnvironmentsUsing Off the Shelf Cellular Handsets[C]//Proceedings of2010 International Conference on Consumer Electronics.Las Vegas,USA:[s.n.],2010.
  • 7Morris B T,Trivedi M M.Trajectory Learning for ActivityUnderstanding:Unsupervised,Multilevel,and Long-termAdaptive Approach[J].IEEE Transactions on Pattern Analysisand Machine Intelligence,2011,33(11):2287-2301.
  • 8Yuan P H,Yang K F,Tsai W H.Real-time Security MonitoringAround a Video Surveillance Vehicle with a Pair of Two-camera Omni-imaging Devices[J].IEEE Transactions onVehicular Technology,2011,60(8):3603-3614.
  • 9Lin Huei-Yung,Wang Ming-Liang,Huang Chi-Chang,et al.Intelligent Surveillance Using an Omnidirectional CCDCamera[C]//Proceedings of International Conference onAutomatic Control.Taipei,China:[s.n.],2005.
  • 10汤一平,叶永杰,朱艺华,顾校凯.智能全方位视觉传感器及其应用研究[J].传感技术学报,2007,20(6):1316-1320. 被引量:49

二级参考文献23

  • 1杨继华,严国萍.基于嵌入式Linux与S3C2410平台的视频采集[J].单片机与嵌入式系统应用,2004,4(11):69-71. 被引量:29
  • 2左文明.连通区域提取算法研究[J].计算机应用与软件,2006,23(1):97-98. 被引量:31
  • 3田国会.家庭服务机器人研究前景广阔[J].国际学术动态,2007(1):28-29. 被引量:21
  • 4BOBICK, DAVIS J. Real-time recognition of activity using temporal templates[ C]// Proceedings of the IEEE Conference on Applications of Computer Vision. Sarasota, Florida, 1996: 39-42.
  • 5MUN Wailee. Model-Based approach for estimating human 3D poses in static images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(6): 905-916.
  • 6MA G, LIN X. Typical sequences extraction and recognition [J ]. Lecture Notes in Computer Vision (LNCS), 2004, 3058 : 60-71.
  • 7KOJIMA A. Generating natural language description of human behaviors from video images [ C]//IEEE International Conference on Patern Recognition. Barcelona: IEEE Press, 2000: 728-731.
  • 8ISMAIL HARITAOGLU, DAVID HARWOOD, LARRY SDAVIS. W4: real-time surveillance of people and their activities [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(8) :809-830.
  • 9Developing a managed integrated long-term care system care system for florida.http://www.pepperinstitute.org/images/Annual%20Report2002-2003.pdf.
  • 10Barger T.Health status monitoring through analysis of behavioral patterns[C]//Proceedings of the 8th Congress of the Italian Association for Artificial Intelligence (AI*IA) on Ambient Intelligence.Pisa,Italy:Springer-Verlag,September 2003.

共引文献70

同被引文献31

引证文献6

二级引证文献13

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部