一個自動監視追蹤系統在保全監視的應用上扮演了一個重要的角色。在本論文的研究中，我們發展了一個即時監視追蹤系統來追蹤移動的物體；例如，人、動物、車輛等。
我們的即時監視追蹤系統分成三個階段。第一階段是利用背景相減法偵測移動的影像點。在這個方法中，我們建立一個適應性的背景，這個背景能夠解決亮度改變及凌亂物件重複移動的問題。第二階段是移除陰影及雜訊，以減少對系統準確性的影響。第三階段是利用前景物件的色彩及形狀去構建一個前景物件，並且利用前景物件的特徵值比對、追蹤、及預測移動物件的下一個位置。
在實驗中，我們考慮到幾種不同的天氣；例如，晴天、陰天、多雲、雨天、黃昏、和夜晚，及不同的背景；例如，建築物、樹葉、道路等。從實驗的結果中，我們發現我們的系統都能在不同的天氣和不同的環境中準確的追蹤各種移動物件。

An automatic surveillance tracking system plays an important role in security applications. In this thesis, we develop a real-time surveillance system for tracking moving objects, like people, animals, vehicles, etc.
Our system consists of three parts. In the first part, we use the background subtraction technique to detect the moving pixels. In the method, we build an adaptive background to deal with the problems of lighting change, and repetitive motions from clutter. In the second part, we remove the shadow and noise in the images to improve the system accuracy. In the third part, we construct the foreground objects with color and shape information. We also use foreground objects’ characteristic to match, track, and predict the position of the moving object.
In the experiments, we consider several different weather conditions such as sunny, cloudy, dusky, rainy hours, and night, and different backgrounds like building, tree leaves, roads, and monitor screens. From the experimental results, we find that the proposed approach can accurately detect and track different moving objects in the different weather conditions, and environments.

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