會議論文
| 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 | en |
| 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 | USA |
| 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 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/39010 ) |