現今，利用手勢作為直覺化的操作方式已越來越受歡迎，這樣的技術應用在人機互動系統、監控系統及體感遊戲等多方面。其簡單又直覺的操作方式，將漸漸地取代傳統遙控器和輸入裝置的使用。在本論文中，我們提出一個基於膚色區塊資訊輔助之即時手勢追蹤與辨識系統，其辨識程序包含人臉辨識、手部偵測、手部追蹤及手勢辨識，以達到直覺化操作的目的。為了提高準確度，我們利用膚色區域移動來校正傳統CamShift演算法追蹤結果。而本論文所提之方法可辨識四種的動態手勢，分別為左揮、右揮、上揮、下揮等動作。在實驗中，我們透過十個受測者左右手的手勢來驗證系統。實作結果證明本研究是有效地且大幅提高了傳統CamShift追蹤演算法的準確度，也不會犧牲太多計算成本，並且能解決仿色系干擾的問題。本文提出的手勢追蹤的技術不僅可以應用在人機互動系統中，也可以應用於虛擬實境的物體追蹤以改良使用者體驗。

Nowadays, intuitive operation modes with the use of gestures have become more and more popular in many applications, such as human-computer interaction, surveillance, and gaming. Because of its convenient and intuitive manipulation, traditional remote and input device control are going to be replaced with hand-gesture based controllers gradually. In this thesis, we propose a real-time hand tracking and gesture recognition system based on skin color region location, and the recognition process comprises the face detection, hand detection, hand tracking, and gesture recognition. For better accuracy, we take the location of detected skin color regions to correct the tracking results from traditional CamShift algorithm. Four dynamic hand gestures consisting of leftward, rightward, upward and downward are able to be recognized. In the experiment, the performance of the proposed system was verified for both right and left hands for ten different users. The experiment results show that our proposed approach is effective, with highly increased recognition accuracy, without wasting too many computations, and can avoid the fail to track problem under the situation that some areas in the background have the similar color distribution as the target. The techniques developed in this study can not only be used in human-computer interaction, but also be applied to augmented reality application to make the user experience much better than before.

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