為了監控環境，我們需要連續不間斷地儲存監視影片，而龐大的影片儲存空間和如何有效率地瀏覽長時間影片便成為很重要的問題。為了解決這些問題，我們提出了一種新的監視影片摘要方法，是在即時的前提之下，將前景物體依照時間先後順序重新排列位置與其出現的時間。而為了擷取出前景物體，我們提出了基於亮度不變的前景擷取方法，以及時空的體積切割方法。相較於傳統的影片摘要，我們的方法可以直接應用在線上的串流監視影片，並且在不必篩選過整段影片的前提下就能產生摘要影片。

In order to monitor environments, continuously storing surveillance videos is required. Enormous storage of videos and how to browse long-time videos become important problems. To solve these problems, we propose a novel surveillance video synopsis method to chronologically rearrange positions and appearing frames of foreground objects in real-time. To extract foreground objects, illumination invariant foreground extraction and spatial-temporal volumetric cut are proposed. Comparing with traditional synopsis approaches, our method can directly be applied to online streaming surveillance videos and generate synopsis videos without screening the whole videos.

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