公共場合的社會安全問題在現今愈變愈重要，人身安全的問題像是物品失竊或是遺失等，有時遺留的物品可能需要引起群眾疏散等危險警訊，因此如何偵測及預防此類的問題成為目前發展中的重要議題。在這篇論文提出了應用在開放空間的數位監控系統上之及時物件追蹤與區分系統，此系統能追蹤出現在監控畫面中的人和物，並且偵測異常行為。首先提出一個新的演算法來訓練出一張背景圖，並用背景和目前畫面間的色彩差異性來擷取出所感興趣的物件，再對這些物件運用中心點來比對出其在不同畫面中所出現的位置加以追蹤。因為畫面中通常有多個人同時存在，所以系統同時會觀察物件間的互動，是否有合併或是分離的現象，若有人群合併後再度分離，系統會對此種情況作判別以區分物件。最後，針對人身安全問題，系統對於失竊及遺留物品等異常情況作偵測，當此種異常狀況發生時，系統會送出警訊給監控者並加以記錄。此追蹤系統應用上述之演算法，能即時地追蹤出現的人物。

Recently, social security problem in the public place becomes more and more important, human security like stealing, losing and some dangerous actions which may need to cause evacuation. How to detect and prevent them is a significant issue. This Thesis proposes an automatic surveillance system for tracking objects and detecting abnormal situation in open space. Usually, the foreground regions will be determined by the trained background. Therefore, a new algorithm is first proposed to estimate background. Then, the system can track the interesting objects by matching method frame by frame. And it not only can track people, but also can discriminate people if they move away after move toward from each other. Finally, the system detects if any person behaves abnormal, such as stealing the object or leaving the bag in the scene. With above algorithms, the system can track people in real time.

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