建立一套智慧型監控系統，其能夠自動地分析影像來偵測出在無人注意的環境之中所被置放的遺留物，並且亦能夠自動地提供關鍵畫面以代替利用人力資源來監控環境。為了偵測並描述完整之遺留物事件，希望不但能偵測到遺留物之外，還能知道遺留物是誰遺落下來的，並且用關鍵畫面以描述整個遺留物事件。
本篇論文將系統分為三個主要部份，第一部份利用兩層的背景架構與背景時間差異法找出靜態的場景變化，結合邊緣資訊和特徵，使用倒傳遞類神經網路分類，以偵測出場景之中的遺留物。第二部分是先統計追蹤物的顏色分佈機率，再透過比對分析其身上是否有物品缺失，當偵測到有物品缺失之後，會對此缺失的物品建立一個混合高斯模型一同與影像建入資料庫中。以上兩部份為平行獨立偵測，當系統偵測到有遺留物的同時也偵測到有人身上有物品遺失之後，系統才會進入第三部份,利用偵測到的遺留物資訊與資料庫中的模型進行比對，搜尋是否有可描述此遺留物事件的關鍵影像。
一旦有遺留物被偵測出來，或是有人遺失物品被偵測到，系統皆會發出警訊，使相關人員提高警覺或相關反應措施。若同時有兩種警訊觸發，此時系統會再去判斷兩個警訊的關聯性，若確認為同一事件，便會提供關鍵影像以讓相關人員能夠立即的做出反應。由實驗可證實所提出偵測遺留物的方法是可行且有效的。

In this thesis, an intelligent video-based surveillance system for the detection of dangerous situations related to the presence of abandoned objects in unattended or guarded environment is presented. In the proposed system, image processing content-based retrieval capabilities have been added to make the operator inspection task easier. When a potential abandoned object event is detected, the operator is notified and the system provides a keyframe for interpreting the incident.
In addition to tracking a moving person and deciding if he drops an object automatically, the system also detects the presence of abandoned object in a monitored area simultaneously. Depending on the detection of either an abandoned object or someone abandoning an object, different alarms will be signaled. Then, the system finds the relationship between the causes of the alarms. If it is verified that someone has lost the abandoned object, in other words, the owner and abandoned objects are detected, the system will alert the operator and provide him the keyframe, i.e., semantic information of which relating to both of the dangerous object and the person who left it in the surveillance environment.
Experimental results are illustrated in terms of abandoned object detection, owner detection, keyframe detection, the probability of correct detection of abandoned objects as well as examples of abandoned objects event sequences. The results demonstrate that the proposed system is feasible and effective in abandoned object detection.

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