博碩士論文 995202056 詳細資訊




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姓名 林紘毅(Hung-Yi Lin)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 Kinect於英語互動學習系統之應用
(An Application of Kinect inAn English Interactive Learning System)
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摘要(中) 本論文設計了兩個應用Kinect於英語互動學習的系統,第一個系統是擴增實境 (Augmented Reality) 系統,輔助老師的英語單字教學。本系統經由 Kinect 來抓取人體停止、前進、後退、左轉以及右轉的姿勢,透過無線射頻傳送指令到自走車,讓自走車行走於虛擬的英語拼單字遊戲板上,藉此學習英文單字,並且能夠讓孩童藉由遊戲來互相切磋比較,進而互相討論與學習,讓孩童能夠寓教於樂。本系統還藉由直覺化的操作,讓自走車控制能夠更符合人性。
第二個系統是機器人互動學習系統,希望藉由本系統來輔助老師上課時使用全肢體反應教學法(Total Physical Response)來教學。本系統由 Kinect 抓取人體的骨架資訊,透過動態時間校正 (Dynamic Time Warping, DTW) 或是隱藏式馬可夫模型 (Hidden Markov Model, HMM) 來判斷做的動作是否正確。本系統提供老師方便上課教學的編輯介面,並且可以讓學生透過老師的幫助,自行使用本系統讓學生能夠自行探索動作和英語的意義,藉由肢體動作以及口語表達出正確的英文語意,並且輔以機器人來互動學習,讓學習是由真實的口語以及動作來輔助學生學習英文的意義並非單純的填鴨式學習。
摘要(英) This thesis designed two applications on Kinect interactive English learning system; the first system is Augmented Reality system, aim to assist teachers in English vocabulary teaching. This system catch skeleton through Kinect for stop, forward, backward, turn left and right, through RF transmission commend to the cars. Cars can drive in virtual English word games to help student learn English words, and allows children to learn from each other by game, and then discuss with each other and learning so that children can be edutainment. This system also represents an intuition car control, can be more consistent with humanity.
The second system is Robot interactive learning system, to help teachers in class using the Total Physical Response. This system catch skeleton through Kinect, through Dynamic Time Warping or Hidden Markov Model to determine the action is correct or not. This system provides the teacher convenient teaching editing interface, and allows the students explore their own movements and English meaning himself. We supply the robot to interactive learning, so that learning in real-spoken language and action to assist students to learn English meaning is not simply spoon-fed learning.
關鍵字(中) ★ TPR教學
★ 動態時間校正
★ 隱藏式馬可夫模型
★ 擴增實境
★ 數位學習
關鍵字(英) ★ Dynamic Time Warping
★ Hidden Markov Model
★ Digital Learning
★ Augmented Reality
★ Total Physical Response
論文目次 中 文 摘 要 i
ABSTRACT ii
致 謝 iii
目錄 iv
圖目錄 vii
表目錄 x
第一章、緒論 1
1-1研究動機 1
1-2研究目的 2
1-3論文架構 3
第二章、相關研究 4
2-1數位學習 4
2-2全肢體反應教學 6
2-3 Kinect 相關應用 7
2-4 姿勢辨識相關應用 9
第三章、擴增實境系統 13
3-1系統架構介紹 13
3-2軟體以及介面介紹 14
3-2-1 Kinect 端軟體介紹 14
3-2-2 攝影機端軟體介紹 17
3-2-3 遊戲端軟體介紹 20
3-3硬體介紹 26
3-3-1無線射頻介紹 27
3-3-2電腦傳送端介紹 30
3-3-3自走車介紹 32
3-3-4紅外線燈板以及攝影機介紹 34
3-3-5 Fujitsu MB9B506R 介紹 35
3-4研究方法與步驟 39
3-4-1 手勢操作演算法 39
3-4-2 自走車定位演算法 42
3-5實驗 47
3-5-1 手勢實驗 47
3-5-2 操控性實驗 47
第四章、機器人互動學習系統 50
4-1系統架構介紹 50
4-2軟體以及介面介紹 51
4-2-1情境編輯模式 54
4-2-2動作編輯模式 55
4-2-3練習模式 59
4-2-4情境模式 60
4-2-5紀錄模式 62
4-3硬體介紹 63
4-4研究方法與步驟 65
4-4-1 骨架以及骨架的前處理 65
4-4-2 動態時間校正演算法 75
4-4-4 隱藏式馬可夫模型演算法 79
4-4-5 語音辨識 83
4-5實驗 84
4-5-1擷取實驗 85
4-5-3動態時間校正以及隱藏式馬可夫模型 87
第五章、結論暨未來展望 89
第六章、參考文獻 91
附錄一、各種動作圖像 96
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指導教授 蘇木春(Mu-Chun Su) 審核日期 2012-7-25
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