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      • Department of Computer Engineering
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      HMM based falling person detection using both audio and video

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      Author
      Töreyin, U. B.
      Dedeğlu, Y.
      Çetin, A. Enis
      Date
      2005
      Source Title
      Lecture Notes in Computer Science
      Print ISSN
      0302-9743
      Electronic ISSN
      1611-3349
      Publisher
      Springer
      Volume
      3766
      Pages
      211 - 220
      Language
      English
      Type
      Article
      Item Usage Stats
      128
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      150
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      Abstract
      Automatic detection of a falling person in video is an important problem with applications in security and safety areas including supportive home environments and CCTV surveillance systems. Human motion in video is modeled using Hidden Markov Models (HMM) in this paper. In addition, the audio track of the video is also used to distinguish a person simply sitting on a floor from a person stumbling and falling. Most video recording systems have the capability of recording audio as well and the impact sound of a falling person is also available as an additional clue. Audio channel data based decision is also reached using HMMs and fused with results of HMMs modeling the video data to reach a final decision.
      Permalink
      http://hdl.handle.net/11693/27290
      Published Version (Please cite this version)
      https://doi.org/10.1007/11573425_21
      Collections
      • Department of Computer Engineering 1368
      • Department of Electrical and Electronics Engineering 3524
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