近幾年來人機互動研究變的非常熱門，特別是在教育、遊憩及醫療保健方面，在先前的研究當中，我們提出了一個應用於電視遙控器以Kinect為主的手寫數字辨識，然而當時的辨識率只有86.7%，這促使我們想要去改善它的辨識率，因此，在本論文中，我們提出一個多分段及縮放編碼技術，實驗結果證明，此方法可以提高辨識率至94.6%。
除此之外，我們還想擴充此系統的實用性，所以在本文中，我們還提出應用於智慧型手機之改良式以Kinect為主的空中手寫數字辨識，當使用者手上並不乾淨時，可利用此系統不用接觸手機即可撥出電話，這能有效解決生活上會遇到的問題。

Human-computer interaction has been much popular in recent years, especially in the field of entertainment and education. In our previous work, we presented a method of Kinect-based mid-air handwritten digit recognition for a potential application to TV remote controllers. Nevertheless, its recognition accuracy is only about 86.7%. In this thesis, we propose an improved method based on multiple segments and scaled coding. Experimental results show that the proposed method can elevate the accuracy up to 94.6%.
Furthermore, we also present two applications combined with our improved method on Android smart phones. This system can be applied to dial without touching the smart phone. This can be implemented in the kitchen or hospital when user's hands are unable to touch the screen.

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[2] Kinect參閱微軟官網-Kinect 應用程式開發入門 http://msdn.microsoft.com/zh-tw/hh367958.aspx
[3] Wii參閱自維基百科全書http://zh.wikipedia.org/wiki/Wii
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[8] 林宗勳，Support Vector Machines 簡介，http://www.cmlab.csie.ntu.edu.tw/~cyy/learning/tutorials/SVM2.pdf
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[22] K最相鄰分類法介紹 http://mirlab.org/jang/books/dcpr/prKnnc.asp?title=5-2%20K-nearest-neighbor%20Classifiers&language=chinese
[23] Light Coding技術介紹 http://www.techbang.com/posts/2936-get-to-know-how-it-works-kinect