A Hybrid Model Using Hidden Markov Chain and Logic Model for Daily Living Activity Recognition

We detail the solution to the UCAmI Cup Challenge to recognizing on going activities at home from sensor measurements. We use binary sensors and proximity sensor measurements for the recognition. We use an hybrid strategy, combining a probabilistic model and a definition-based model. The former cons...

詳細記述

書誌詳細

出版年:	Proceedings
主要な著者:	Paula LAGO, Sozo INOUE
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2018-10-01
主題:	activity recognition daily living activities neural networks hidden markov models event recognition
オンライン･アクセス:	https://www.mdpi.com/2504-3900/2/19/1266