Hybrid Model-Based Motion Recognition for Smartphone Users

Title
Hybrid Model-Based Motion Recognition for Smartphone Users
Authors
신범주김철기김재헌이석기창돈이택진
Keywords
Hybrid model; motion recognition; decision tree; artificial neural network; smartphone
Issue Date
2014-12
Publisher
ETRI journal
Citation
VOL 36, NO 6, 1016-1022
Abstract
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 (DTs) and artificial neural networks (ANNs) 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.
URI
http://pubs.kist.re.kr/handle/201004/48137
ISSN
12256463
Appears in Collections:
KIST Publication > Article
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