視訊濃縮(或稱視頻摘要技術)主要的用途為去除長時間視訊中空間域以及/或者時間域的冗餘資訊並進一步藉由改變原始影片中之物件串列時間空間關聯性來達成視訊濃縮之目的。現今存在的視訊濃縮技術皆有一前提，假設所有物件串列(同一物件不同時間的集合，例如一行走的行人是由上百張行走的"照片"所組合而成)皆是獨立的並且可以從原始影片中完美的取出，可是此一前提在現實監視影像中是很難達成的，因目前尚無完美背景濾除演算法及物件追蹤演算法保證能克服強烈的光影變化或是因物件重疊所導致的去背景和追蹤失敗。另外，前人提出的濃縮視訊演算法所使用到的能量最小化演算法有著高計算複雜度的缺點，進而影響到此技術的實用性。
有鑑於此，本論文提出高效率且無失真視訊濃縮技術分為以下四個部分：1) 提出基於三維空間軌跡投影之物件串列分群演算法，解決前人因物件破碎或物件追蹤失敗所導致的濃縮影片不流暢之問題。2) 提出物件串列之最小重疊率位移演算法，克服前人採用能量最佳化所造成的效率低落問題。3) 針對濃縮影片時間長度的問題，提出全域時域移動及時地調整濃縮時間長度，使得在瀏覽濃縮影片上更加靈活。4) 物件串列特性檢索，透過物件串列大小，方向，顏色，所經過的區域的檢索，縮短使用者在找尋特別事件所花費的時間。
最後實驗結果也顯示本論文所提出的基於三維空間軌跡投影分群及物件分類之視訊濃縮演算法除了可以達到即時處理外，其產生的濃縮視訊可以克服物件追蹤失敗在濃縮視訊中所產生的不流暢現象。

Nowadays, the video surveillance systems have become popular, and are deployed in every corner of our environment, such as in the school, airport, street, etc. It generates huge data consistantly. Thus, browsing and searching for a specific event from this database becomes challenging. To reduce the efforts by manually searching targets, the video synopsis technique was proposed to efficiently capture the dynamic behavior of a specific object with limited time period. The video synopsis method provides a condensed video by removing the spatial or temporal redundancies. This technique maintains and records all the activities completely in the original video. Some former methods have been proposed, yet they require long computational time. In addition, the blanking effect is accompanied. To overcome the above issues, a new efficient trajectory-based video synopsis is proposed in this thesis. It consists of four parts, including 1) trajectory-based object classification to keep the tubes continually and avoid the blanking effect on the synopsis video; 2) Minimum Overlap (MO) algorithm for the objects tubes temporal position in synopsis video, 3) Global Temporal Shifting (GTS) processes to make the tubes with the temporal-domain flexibility, and 4) Attributes search for a efficient way to enable a user locating specific events precisely and efficiently. As demonstrated in the experimental result, the proposed video synopsis effectively produces smooth synopsis videos without blanking, jumping, and ghosting issues.

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