眼睛的定位與追蹤在許多的人機介面應用中扮演相當重要的角色，諸如以凝視為基礎的通訊與控制、使用人類瞳孔來辨識身份的安全系統(虹膜辨識系統)等等，而眨眼偵測的加入，可使得人機介面的應用更為多樣化，例如眼控人機介面、電腦使用者疲倦偵測，以及智慧型交通系統中的駕駛人疲倦偵測等等。在本論文中，我們使用放置在電腦螢幕上的視訊攝影機，即時擷取使用者以及週遭工作環境的影像，建立一套非接觸式的眨眼偵測系統，應用的技術包括人臉偵測、眼睛定位、眼睛追蹤，以及眨眼偵測等部份。於人臉偵測的部份，我們使用光源補償技術降低環境光源對彩色影像的影響，接著利用色調值進行膚色抽取與膚色二值化影像的建立，然後利用數理型態學運算與連接相連元件方法框出候選臉部區塊，並利用人臉的基本特性來完成影像中的人臉偵測。在眼睛定位的部份，我們直接將臉部區域直接代入已訓練過的支向機中作分類運算以找出眼睛區域。在找到眼睛之後，我們將眼睛追蹤與眨眼偵測同時進行，其中利用粒子濾波器技術對眼睛區域作追蹤的動作，且利用睜眼及閉眼之彩色直方圖比對直接對所追蹤的眼睛作眨眼偵測。經由實驗結果顯示，我們的系統可以有效地追蹤眼睛並偵測眨眼的狀況。

In many applications of human-computer interfaces, the eye location and tracking techniques play a quite important role; for example, gaze-based communication and control, iris-based biometric recognition, and so on. In addition to this, the incorporation of blinking detection has made such human-computer interfaces more diversified like the eye-control human computer interface, computer-user fatigue detection, and driver fatigue detection in the intelligent traffic system. In this thesis, we have developed a non-contact eye’s blinking detection system that uses a video camera on the top of a computer monitor to capture the image of the user as well as the environment in real time. This system consists of three main processing phases: face detection, eye location and tracking, and blinking detection. Regarding the face detection, a light compensation technique is first employed to diminish the influence of light sources on color images. After color model converting, the hue component is adopted to extract skin colors and build up a skin binary image. Mathematical morphological operations and connected component labeling methods are further exploited to find candidate face regions which are verified by the priori facial feature information. In the eye location and tracking phase, a support vector machine is applied to searching eye regions which provide geometric information for eye tracking by a particle filter in image sequences. As to the blinking detection, the color histograms of eye regions are used to distinguish opening eyes from closing ones. The experimental results reveal that our developed system can trace eyes and detect the blinking effectively.

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