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  • 标题:Hybrid Model-Based Motion Recognition for Smartphone Users
  • 本地全文:下载
  • 作者:Shin, Beomju ; Kim, Chulki ; Kim, Jae Hun
  • 期刊名称:ETRI Journal
  • 印刷版ISSN:1225-6463
  • 电子版ISSN:2233-7326
  • 出版年度:2014
  • 卷号:36
  • 期号:6
  • 页码:1016-1022
  • DOI:10.4218/etrij.14.0113.1159
  • 语种:English
  • 出版社:Electronics and Telecommunications Research Institute
  • 摘要:This paper presents a hybrid model solution for user motion recognition. The use of a single classifier in motion recognition models does not guarantee a high recognition rate. To enhance the motion recognition rate, a hybrid model consisting of decision trees and artificial neural networks is proposed. We define six user motions commonly performed in an indoor environment. To demonstrate the performance of the proposed model, we conduct a real field test with ten subjects (five males and five females). Experimental results show that the proposed model provides a more accurate recognition rate compared to that of other single classifiers.
  • 关键词:Hybrid model;motion recognition;decision tree;artificial neural network;smartphone
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