教師資料查詢 | 類別: 會議論文 | 教師: 蘇木春 SU MU-CHUN (瀏覽個人網頁)

標題:A static hand gesture recognition system using a composite neural network
學年85
學期1
發表日期1996/09/08
作品名稱A static hand gesture recognition system using a composite neural network
作品名稱(其他語言)以複合式類神經網路為架構之靜態手語辨識系統
著者蘇木春; Su, Mu-chun; Jean, Woung-fei; Chang, Hsiao-te
作品所屬單位淡江大學電機工程學系
出版者Institute of Electrical and Electronics Engineers (IEEE)
會議名稱Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
會議地點New Orleans, LA, USA
摘要A system for the recognition of static hand gestures is developed. Applications of hand gesture recognition range from teleoperated control to hand diagnostic and rehabilitation or to speaking aids for the deaf. We use two EMI-Gloves connected to an IBM compatible PC via hyperrectangular composite neural networks (HRCNNs) to implement a gesture recognition system. Using the supervised decision-directed learning (SDDL) algorithm, the HRCNNs can quickly learn the complex mapping of measurements of ten fingers' flex angles to corresponding categories. In addition, the values of the synaptic weights of the trained HRCNNs were utilized to extract a set of crisp IF-THEN classification rules. In order to increase tolerance on variations of measurements corrupted by noise or some other factors we propose a special scheme to fuzzify these crisp rules. The system is evaluated for the classification of 51 static hand gestures from 4 “speakers”. The recognition accuracy for the testing set were 93.9%
關鍵字
語言英文
收錄於
會議性質國際
校內研討會地點
研討會時間19960908~19960911
通訊作者
國別美國
公開徵稿
出版型式紙本
出處Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on (Volume:2 ), pp.786-792
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