한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제18권9호
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  • Pages.2101-2108
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  • 2014
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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단순 임계치와 은닉마르코프 모델을 혼합한 영상 기반 낙상 알고리즘

Video-based fall detection algorithm combining simple threshold method and Hidden Markov Model

  • Park, Culho (Department of Electrical, Electronic and Control Engineering and IITC, Hankyong National University) ;
  • Yu, Yun Seop (Department of Electrical, Electronic and Control Engineering and IITC, Hankyong National University)
  • 투고 : 2014.06.03
  • 심사 : 2014.07.16
  • 발행 : 2014.09.30
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초록

영상 정보를 이용한 자동 낙상 감지 알고리즘을 제안한다. 자동으로 낙상을 감지하기 위한 낙상 특징 파라미터를 추출하기 위해서 영상정보를 광류 방식에 적용하여 움직임 값들을 추출하고 이 움직임 값들에 대한 전체적인 변화의 정도와 기울기, 중심점을 주성분 분석 방법으로 계산한다. 계산된 고유값과 고유 벡터를 사용하여 6가지 낙상 특징 파라미터를 정의한다. 이 낙상특징파라미터가 미리 정해둔 임계값을 초과하는 경우를 낙상으로 판단하는 단순 임계치 방법과 낙상특징파라미터를 은닉 마르코프 모델(Hidden Markov Model; HMM)에 적용시켜 낙상을 판단하는 방법과 단순임계치와 은닉 마르코프 모델을 결합한 낙상 감지 방법을 제안하고 그 결과를 비교 및 분석한다. 단순 임계치와 은닉 마르코프 모델을 결합한 방법은 단순임계치 방법으로 낙상 가능한 행동들을 결정하고 이 결정된 낙상 행동들만을 은닉 마르코프 모델을 적용하여 낙상을 감지한다. 이 방법은 계산량을 줄이면서 감지 정확도를 유지하는 결과를 보인다.

Automatic fall-detection algorithms using video-data are proposed. Six types of fall-feature parameters are defined applying the optical flows extracted from differential images to principal component analysis(PCA). One fall-detection algorithm is the simple threshold method that a fall is detected when a fall-feature parameter is over a threshold, another is to use the HMM, and the other is to combine the simple threshold and HMM. Comparing the performances of three types of fall-detection algorithm, the algorithm combining the simple threshold and HMM requires less computational resources than HMM and exhibits a higher accuracy than the simple threshold method.

키워드

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