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Article Dans Une Revue IEEE Transactions on Automation Science and Engineering Année : 2020

Human Activity Discovery and Recognition using Probabilistic Finite-State Automata

Résumé

Ambient assisted living and smart home technologies are a good way to take care of dependant people whose number will increase in the future. They allow the discovery and the recognition of human’s Activities of Daily Living (ADLs) in order to take care of people by keeping them in their home. In order to consider the human behaviour non-determinism, probabilistic approaches are used despite difficulties encountered in model generation and probabilistic indicators computing. In this paper, a global method, based on Probabilistic Finite-State Automata and the definition of the normalised likelihood and perplexity is proposed to manage ADLs discovery and recognition. In order to reduce the computational complexity, some results about a simplified normalised likelihood computation are proved. A real case study showing the efficiency of the proposed method is discussed.
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Dates et versions

hal-02557589 , version 1 (28-04-2020)

Identifiants

  • HAL Id : hal-02557589 , version 1

Citer

K Viard, M. P. Fanti, G. Faraut, J-J Lesage. Human Activity Discovery and Recognition using Probabilistic Finite-State Automata. IEEE Transactions on Automation Science and Engineering, In press, 17 (4), pp. 2085-2096. ⟨hal-02557589⟩
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