博碩士論文 995202078 詳細資訊




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姓名 李怡臻(Yi-Zhen Li)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 光學式觸控人機介面的手勢分類器設計
(Gesture Classifier Design for Optical Touch Human-Machine Interface)
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摘要(中) 在人機互動中,觸控螢幕裝置是我們用來接收資訊的主要媒介之一,在小尺寸的螢幕技術已經成熟並帶來極為便利的運作模式,相對的大尺寸的觸控面板將會是未來螢幕發展的趨勢,其中如何實現快速及客製化的開發出符合需求的觸控處理器是重要的議題。
本研究提出一個結合時空型態手勢與離散事件型態手勢的泛用途智慧型分類器,此一分類器使用機率神經網路作為時空型態手勢辨識核心,並以PSO演算法作為PNN分類器的學習機制;離散事件手勢辨識是在離散時間軸上辨識連續的手勢狀態轉移。結合這兩種型態手勢,我們使用Grafcet離散事件模型設計出手勢處理器指令集架構,提供手勢應用系統開發者可據以定義並快速生成各種客製化的人機互動界面手勢處理器。
最後我們以醫療床邊照顧系統與IPTV兩個應用為例,根據此手勢處理器指令集架構定義出兩個客製化的手勢辨識處理器。針對新世代消費型電子產品,此一智慧型分類器提供了一個具有高度設計彈性、優異的辨識性能與快速雛形化的手勢辨識與人機互動方法。
摘要(英) In human-computer interaction (HCI) system, the touch display device is one of the main medium to receive information. There are many small-size touch panel current, so the large-size touch panel is the trend . How to establish a fast and customized touch processor becomes important.
We proposed an intelligent classifier which integrates spatial and temporal pattern into discrete event modeling in gesture recognition. We use probabilistic neural network (PNN) as a kernel recognition algorithm, and adding particle swarm optimization (PSO) in the learning phase. As the discrete event modeling is to recognize the continuous-gesture-state transition in the discrete time-slice. To combine these two types of gestures, we use Grafcet discrete event modeling to design the gesture processor instruction set architecture. User can use it to enerate a variety of customized HCI interface gestures processor quickly.
With this gesture processor instruction set architecture, we can define customized gesture recognition processor such as medical bedside care system and IPTV. This intelligent classifier provides an excellent recognition performance, high flexibility and rapid prototype gesture recognition in human-machine interaction application .
關鍵字(中) ★ 光學式
★ 觸控
★ 手勢
★ 自訂手勢
關鍵字(英) ★ touch
★ optical
★ gesture
論文目次 摘要 II
ABSTRACT III
目錄 IV
圖目錄 VII
表目錄 X
第一章 、緒論 1
1.1研究背景與動機 1
1.2論文架構 2
第二章、文獻探討 4
2.1感測器式觸控面板技術 4
2.1.1 電阻式觸控技術 4
2.1.2 電容式觸控技術 6
2.1.3 聲波式觸控技術(acoustic wave analysis) 8
2.1.4 感測器陣列式觸控技術 10
2.2電腦視覺式觸控面板技術 12
2.2.1 純視覺式觸控技術 12
2.2.2 視覺與光學觸控技術 13
2.3觸控電子白板 15
第三章、光學式投影幕觸控 17
3.1構想 17
3.1.1硬體設備及安裝 18
3.1.2系統流程圖 19
3.2觸控偵測和定位演算法 20
3.2.1影像前處理 20
3.2.2觸碰物偵測 23
3.2.3廣角鏡頭校正與角度計算 24
3.2.4觸控點定位 26
3.2.5觸控點校正 26
3.2.6觸控點軌跡平滑化 27
3.3手勢連續座標前處理 29
3.3.1異常座標點濾除 29
3.3.2座標尺度正規化(Scaling) 30
3.3.3座標點插補 31
第四章、手勢辨識處理器設計 33
4.1時空型態手勢辨識 34
4.2 離散事件型態辨識 35
4.3 TS/DE混合手勢指令集設計 37
4.3.1 Grafcet離散事件模型 37
4.3.2 TS/DE混合系統模型 41
4.3.3觸控手勢指令集設計 44
4.3.4 TS/DE混合手勢分類器 53
第五章、手勢辨識處理器應用 56
5.1實驗設備與開發環境 56
5.2觸控手勢實作與驗證 57
5.2.1基本觸控手勢辨識實驗 60
5.2.2複雜觸控手勢實驗 63
5.2.3自訂觸控手勢 67
5.3系統性能分析 71
5.4客製化手勢指令集設計與應用 72
第六章、結論與未來研究方向 76
6.1結論 76
6.2未來研究方向 76
參考文獻 78
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指導教授 陳慶瀚 審核日期 2012-6-27
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