The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cette lettre, nous proposons une nouvelle approche de la reconnaissance de l'activité humaine. Nous présentons une classe de fonctionnalités robustes à l'inclinaison du module de capteur attaché et un modèle de transition d'état adapté à la reconnaissance d'activité basée sur HMM. De plus, des techniques de post-traitement sont appliquées pour stabiliser les résultats de reconnaissance. L'approche proposée montre des améliorations significatives dans les expériences de reconnaissance sur une variété de bases de données sur l'activité humaine.
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Chang Woo HAN, Shin Jae KANG, Nam Soo KIM, "Implementation of HMM-Based Human Activity Recognition Using Single Triaxial Accelerometer" in IEICE TRANSACTIONS on Fundamentals,
vol. E93-A, no. 7, pp. 1379-1383, July 2010, doi: 10.1587/transfun.E93.A.1379.
Abstract: In this letter, we propose a novel approach to human activity recognition. We present a class of features that are robust to the tilt of the attached sensor module and a state transition model suitable for HMM-based activity recognition. In addition, postprocessing techniques are applied to stabilize the recognition results. The proposed approach shows significant improvements in recognition experiments over a variety of human activity DB.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E93.A.1379/_p
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@ARTICLE{e93-a_7_1379,
author={Chang Woo HAN, Shin Jae KANG, Nam Soo KIM, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Implementation of HMM-Based Human Activity Recognition Using Single Triaxial Accelerometer},
year={2010},
volume={E93-A},
number={7},
pages={1379-1383},
abstract={In this letter, we propose a novel approach to human activity recognition. We present a class of features that are robust to the tilt of the attached sensor module and a state transition model suitable for HMM-based activity recognition. In addition, postprocessing techniques are applied to stabilize the recognition results. The proposed approach shows significant improvements in recognition experiments over a variety of human activity DB.},
keywords={},
doi={10.1587/transfun.E93.A.1379},
ISSN={1745-1337},
month={July},}
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TY - JOUR
TI - Implementation of HMM-Based Human Activity Recognition Using Single Triaxial Accelerometer
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1379
EP - 1383
AU - Chang Woo HAN
AU - Shin Jae KANG
AU - Nam Soo KIM
PY - 2010
DO - 10.1587/transfun.E93.A.1379
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E93-A
IS - 7
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - July 2010
AB - In this letter, we propose a novel approach to human activity recognition. We present a class of features that are robust to the tilt of the attached sensor module and a state transition model suitable for HMM-based activity recognition. In addition, postprocessing techniques are applied to stabilize the recognition results. The proposed approach shows significant improvements in recognition experiments over a variety of human activity DB.
ER -