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Posture Recognition Based on Fuzzy Logic for Home Monitoring of the Elderly

Abstract : We propose in this paper a computer vision-based posture recognition method for home monitoring of the elderly. The proposed system performs human detection prior to the posture analysis; posture recognition is performed only on a human silhouette. The human detection approach has been designed to be robust to different environmental stimuli. Thus, posture is analyzed with simple and efficient features that are not designed to manage constraints related to the environment but only designed to describe human silhouettes. The posture recognition method, based on fuzzy logic, identifies four static postures and is robust to variation in the distance between the camera and the person, and to the person's morphology. With an accuracy of 74.29% of satisfactory posture recognition, this approach can detect emergency situations such as a fall within a health smart home.
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-00742239
Contributeur : Yannick Benezeth <>
Soumis le : mardi 16 octobre 2012 - 11:45:01
Dernière modification le : vendredi 17 juillet 2020 - 14:54:04

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Damien Brulin, Yannick Benezeth, Estelle Courtial. Posture Recognition Based on Fuzzy Logic for Home Monitoring of the Elderly. IEEE Transactions on Information Technology in Biomedicine, Institute of Electrical and Electronics Engineers, 2012, 16 (5), pp.974 - 982. ⟨10.1109/TITB.2012.2208757⟩. ⟨hal-00742239⟩

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