标题:Static Hand Gesture Recognition Based on Neighborhood Rough Set
作者:Cui, Zhen-Xing; Yang, Ming-Qiang; Zeng, Wei; Zhuang, Hui-Wei
通讯作者:Yang, MingQiang
作者机构:[Cui, Zhen-Xing; Yang, Ming-Qiang; Zeng, Wei; Zhuang, Hui-Wei] Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Peoples R China.
会议名称:International Conference on Fuzzy System and Data Mining (FSDM)
会议日期:DEC 12-15, 2015
来源:FUZZY SYSTEM AND DATA MINING
出版年:2016
卷:281
页码:122-128
DOI:10.3233/978-1-61499-619-4-122
关键词:Static hand gesture; HOG; PCA; neighborhood rough set; fuzzy neural; network
摘要:Hand gesture recognition has become a major focus of research in the field of human-computer interaction (HCI). This work proposes a static hand gesture recognition system. The Histogram of Oriented Gradients (HOG) was used for feature extraction. The features are reduced by PCA and further reduced using the attribute reduction algorithm in the theory of the neighborhood rough set. Then, the weight of every feature is calculated using the attribute significance algorithm in the theory of neighborhood rough sets. The weighted features are applied as input to the fuzzy neural network to recognize static hand gestures. Experimental results on commonly-referred databases show that the proposed method based on neighborhood rough sets improves the recognition accuracy of fuzzy neural networks.
收录类别:CPCI-S;EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964649168&doi=10.3233%2f978-1-61499-619-4-122&partnerID=40&md5=08e385f700fb679529a2ea487348c7fd
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