Human Activity Recognition using Smart Phone Embedded Sensors: A Linear Dynamical Systems Method

被引：0
|
作者：
Wang, Wen [1 ,2 ]
Liu, Huaping [1 ]
Yu, Lianzhi [1 ,2 ]
Sun, Fuchun [1 ]
机构：
[1] Tsinghua Univ, Dept Comp Sci & Technol, State Key Lab Intelligent Technol & Syst, TNLIST, Beijing 100084, Peoples R China
[2] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai, Peoples R China
来源：
PROCEEDINGS OF THE 2014 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2014年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a novel framework of human activity recognition with time series collected from inertial sensors. We model each action sequence with a collection of Linear Dynamic Systems (LDSs), each LDS describing a small patch of the sequence. A codebook is formed by using the K-medoids clustering algorithm and a Bag-of-Systems (BoS) is developed to represent the time series. A great advantage of this method is that the complicated feature design procedure is avoided and the LDSs can well capture the dynamics of the time series. Our experiment validation on public dataset shows the promising results.
引用
收藏
页码：1185 / 1190
页数：6
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