Implementation of HMM-Based Human Activity Recognition Using Single Triaxial Accelerometer
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E93-A No.7 pp.1379-1383
- Publication Date
- 2010/07/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E93.A.1379
- Type of Manuscript
- LETTER
- Category
- Digital Signal Processing
Authors
Keyword
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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 -
English
