Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/57070
Title: Human and dog movement recognition using fuzzy inference system with automatically generated membership functions
Authors: Chukit Ruanpeng
Sansanee Auephanwiriyakul
Nipon Theera-Umpon
Keywords: Computer Science
Mathematics
Issue Date: 23-Aug-2017
Abstract: © 2017 IEEE. In this paper, the simple movement (walking dog, crawling human, and walking human) recognition system using the Mamdani fuzzy inference system is introduced. The membership functions of each input feature are generated automatically without experts' prior knowledges. The system produces a very high recognition rate, i.e., 93.97%, on the validation set of the cross validation. However, there are some misclassifications between walking dog and crawling human classes. The misclassifications are mainly from the incomplete segmentation of the objects of interest.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030152769&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/57070
ISSN: 10987584
Appears in Collections:CMUL: Journal Articles

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