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研究生:周至濠
研究生(外文):CHIH-HAO CHOU
論文名稱:電腦視覺在手部行為之分析與應用
論文名稱(外文):The Analysis and Application of the Hand’s Behavior with Computer Vision
指導教授:許毅然,彭守道
指導教授(外文):Yih-Ran Sheu, Shou-Tao Peng
學位類別:碩士
校院名稱:南台科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:84
中文關鍵詞:電腦視覺改良式適應性背景相減法察覺移動歷史影像
外文關鍵詞:Computer VisionModified Adaptive Background SubtractionMotion History Image
相關次數:
  • 被引用被引用:4
  • 點閱點閱:217
  • 評分評分:
  • 下載下載:69
  • 收藏至我的研究室書目清單書目收藏:1
現今電腦視覺在人體行為分析的研究受到廣大討論,如何利用行為分析的結果來完成新一代的人機介面,將極具研究的價值。本文利用改良式適應性背景相減法察覺完整的目標物,移動歷史影像紀錄目標物手部移動的歷史軌跡,並分別計算左右手手部移動向量,藉此得到手部行為,我們將應用於發展一套會議系統,透過演講者手部行為分析的結果,控制Powerpoint的換頁與電動式投影幕的上升與下降,證明系統的可行性。
Nowadays, the application of computer vision to human behavior analysis becomes more and more popular. The topic of how to develop human-machine interfaces to interpret the human’s behavior is worth considering.
This research is concerned with using some techniques of computer vision, such as the Modified Adaptive Background Subtraction and Motion History Image, to find out and record the historical movement of the target’s hands. The hand’s behavior can be concluded from analyzing these records.
In this study, the hand’s behavior analysis is applied to a conference system. When speakers wave their hands, this system can immediately output a signal to control the slide page up and down in response to the gestures. In addition, the electronic projection screen can be also controlled by the proposed method.
摘要 iv
英文摘要 v
致謝 vi
目次 vii
表目錄 ix
圖目錄 x
第一章 序論 1
1.1 前言 1
1.2 研究動機及目的 3
1.3 論文架構 5
第二章 相關研究 6
2.1 智慧型監視系統 6
2.2 移動物體的察覺 8
2.2.1 背景相減法 9
2.2.2 時間差值法 10
2.2.3 光流法 13
2.3 動作辨識 15
第三章 移動目標物與移動方向察覺 20
3.1 適應性背景相減法 20
3.2 改良式適應性背景相減法 29
3.2.1 物件標示 31
3.2.2 重疊分類法 33
3.2.3 前景相似度量測 34
3.2.3.1 靜止目標物的外部輪廓 36
3.2.3.2 目前影像與背景模型亮度梯度 38
3.2.3.3 輪廓契合度與前景相似度量測 38
3.2.3.4 靜止物體之背景更新 39
3.3 移動歷史影像 44
第四章 系統架構 47
4.1 系統流程 48
4.1.1 基本動作判斷子系統 49
4.2 硬體與軟體 51
4.2.1 電動投影幕 52
4.2.2 影像擷取卡 53
4.2.3 攝影機 54
4.2.4 投影幕控制板 56
第五章 實驗結果與討論 59
5.1 改良式適應性背景相減法實驗與結果 59
5.1.1 改良式適應性背景相減法移動物體察覺 59
5.1.2 改良式適應性背景相減法之靜止前景更新 62
5.1.3 改良式適應性背景相減法之靜止背景更新 64
5.2 移動歷史影像之移動角度計算 65
5.2.1 右手移動角度計算 65
5.2.2 左手移動角度計算 70
5.2.3 雙手移動角度計算與結果分析 75
5.3 實驗整合與結果討論 77
第六章 結論及未來方向 81
參考文獻 82
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