鍵盤、滑鼠，是操作電腦不可或缺的設備，而隨著時代的進步，輸入設備不再侷限在此之上，如眼動儀的使用，運用眼球追蹤技術來控制滑鼠；語音輸入、辨識系統，能使較不熟悉鍵盤操作的使用者，能夠利用語音輸入設備達到打字的效果；觸控螢幕，讓手機、電腦的操作在手指滑動間即可達成，這些科技的發明，都讓電腦的操作更為人性化。而本研究係使用的微軟Kinect做為輸入端，讓使用者能自行輸入姿勢後再經本系統進行辨識，讓使用者以最直覺且習慣的方式操作電腦。本系統係以軌跡辨識為基礎，收集Kinect所提供的骨架資訊，再以決策樹的方式對使用者所輸入的姿勢進行儲存、分類與辨識，並在不造成使用者負擔的前提之下，以少量的事前訓練姿勢達到一定的辨識效果。

Keyboard and mouse are the essential equipment to control computers. As time goes by, the way of controling computers is changing. For example , Eye tracker uses eye tracking to control mouse; Voice recognition let users use their own voice to input data as keyboard, providing a new way for those who not familiar with keyboard; touching screen, one of the most popular way to control computers and mobile phones, let users controlling their devices by just their fingertips. These technologies provide a more humanistic perspective way controlling computers. Kinect, the input of my research, using the whole body as a controller, with the corresponding special design system, this can reach a more intuitive way to control computer. In this research, We use Trajectory based approach and collecting skeleton data from Kinect to store and categorize user’s gestures. In this research, we construct a decision-tree-like structure to recognize users’ gesture, hoping using the less training data to get good preciseness.

[1]孫秀敏，論多媒體教學在對外漢語教學中的重大意義，中國華文教育網：http://big5.hwjyw.com/。
[2]李韋廷(2010)，人體姿勢判斷系統應用於投影片控制，未出版碩士論文，國立臺灣師範大學資訊工程所，臺北市。
[3]李振遠(2011)，基於背景模型的人體姿勢判斷系統，未出版碩士論文，國立臺灣師範大學資訊工程所，臺北市。
[4]Leonard E. Baum, Ted Prtrie,” Statistical Inference for Probabilistic Functions of Finite State Markov Chains”, Institute of Defense Analyses, Princetion, N.J.,April. 1966.
[5]B-W. Min, H.-S. Yoon, J.Soh, Y.-M Yang, and T.Ejima, “Hand gesture recognition using hidden Markov models,” Systems, Man and Cybernetics, ‘Computational Cybernetics and Simulation’, IEEE International Conference on Florida, USA, pp.4232-4235, Oct. 1997.
[6]J.Lafferty,A.McCallum, and F.Pereira, “Conditional Random Fields:Probabilistic Models for Segmenting and Labeling sequence data,” International conference on Machine Learning, Williams College, Williamstown, MA,USA,pp.282-289,June 2001.
[7]A.Quattoni,S.Wang,L.-P.Morency,T.Dattell, and D.Demirdjian,”Hidden Conditional Random Fields for Gesture Recognition,” Computer Vision and Pattern Recognition, IEEE Computer Society Conference, New York, USA pp.1521-1527,June 2006.
[8] Albitar, I.C., Graebling, P., Doignon, C., “Robust Structured Light Coding for 3D Reconstruction”, Computer Vision, 2007. ICCV 2007. IEEE International Conference,Oct 2007.
[9] 微軟Kinect官方網站，http://www.xbox.com/en-US/KINECT.
[10] Jacob O. Wobbrock., Andrew D. Wilson., Yang Li,” Gestures without Libraries, Toolkits or Training:A $1 Recognizer for User Interface Prototypes” ACM International Conference ,Newport, Rhode Island, USA. UIST’07, October 7-10, 2007.
[11] Jamie Shotton, Andrew Fitzgibbon,, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, Andrew Blake,” Real-Time Human Pose Recognition in Parts from Single Depth Images”, Microsoft Research Cambridge & Xbox Incubation, April 2011.
[12] Y. Amit and D. Geman. Shape quantization and recognition with randomized trees. Neural Computation, 9(7):1545–1588, 1997.
[13] George A. Miller, The Magical Number Seven, Plus or Minus Two Some Limits on Our Capacity for Processing Information, Harvard University, May 1955.
[14] Leap Motion官方網站，http://leapmotion.com/。