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http://dx.doi.org/10.6109/jkiice.2014.18.9.2101

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)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.9, 2014 , pp. 2101-2108 More about this Journal
Abstract
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.
Keywords
fall detection; optical flow; principal component analysis(PCA); Hidden Markov Model(HMM); fall-feature parameters;
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Times Cited By KSCI : 1  (Citation Analysis)
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