模式识别与人工智能
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  2018, Vol. 31 Issue (7): 653-661    DOI: 10.16451/j.cnki.issn1003-6059.201807008
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Daily Behavior Recognition with Single Sensor Based on Functional Time Series Data Modeling
SU Benyue1,2, ZHENG Dandan1,2, SHENG Min2,3
1.School of Computer and Information, Anqing Normal University, Anqing 246133
2.The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing 246133
3.School of Mathematics and Computational Science, Anqing Normal University, Anqing 246133

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Abstract  In inertial sensor based human activity recognition, the periodic and temporal characteristics are often ignored in the traditional algorithms, and there are corresponding requirements for the size of the sliding window to extract features. In this paper, a recognition algorithm based on functional data analysis and hidden Markov model for periodic behavior is proposed with a single wearable sensor placed on the waist for human daily activities. Firstly, the functional data analysis method is used to fit the motion capture data of periodic daily activities, and then the single cycle data are extracted after fitting. Secondly,based on the single periodic behavior data, a hidden Markov model describing each daily behavior process is established. Finally, human activities are classified with the maximum likelihood .Compared with the multisensor human activity recognition methods, the proposed method is able to effectively classify 8 daily activities via single sensor with high recognition rates in both user dependent mode and user independent mode.
Key wordsHuman Activity Recognition      Wearable Motion Capture System      Functional Data Analysis      Hidden Markov Model      Single Sensor     
Received: 11 February 2018     
ZTFLH: TP 391  
Fund:Supported by National Natural Science Foundation of China(No.61603003,11471093), Fund for “Integration of Cloud Computing and Big Data, Innovation of Science and Education” of Ministry of Education of China (No.2017A09116), Anhui Provincial Universities Outstanding Top-notch Talent Cultivation Project(No.gxbjZD26)
Corresponding Authors: SU Benyue(Corresponding author), Ph.D., professor. His research interests include graphic image processing, virtual reality and machine learning.   
About author:: ZHENG Dandan, master student. Her research interests include pattern recognition and human activity recognition.SHENG Min, Ph.D., professor. Her research interests include image processing and machine learning.
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SU Benyue
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SU Benyue,ZHENG Dandan,SHENG Min. Daily Behavior Recognition with Single Sensor Based on Functional Time Series Data Modeling[J]. , 2018, 31(7): 653-661.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201807008      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I7/653
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