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2008/9/24.

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EFFICIENT VIDEO SIMILARITY MEASUREMENT AND SEARCH, Department of Electrical Engineering and Computer Sciences University of California Berkeley, CA 94720{cheungsc, avz}@eecs.berkeley.edu ICIP 2000

ABSTRACT
We consider the use of meta-data and/or video-domain methods to detect similar videos on the web. Meta-data is extracted from the textual and hyperlink information associated with each video clip. In video domain, we apply an efficient similarity detection algorithm called video signature. The idea is to form a signature for each clip by selecting a small number of its frames that are most similar to a set of random seed images.
We then apply a statistical pruning algorithm to allow fast detection on very large databases. Using a small ground-truth set, we achieve 90% recall and 95% precision using only 8% of the total number of operations required without pruning.
For a database of around 46,000 video clips crawled from the web, video signature technique significantly outperforms meta-data in precision and recall. We show that even better performance can be achieved by combining them together. Based on our measurements, each video clip in our database has, on average, 1.53 similar copies.

A fast shot matching strategy for detecting duplicate sequences in a television stream ACM International Conference Proceeding Series; Vol. 16
要從學校圖書館進去抓.

ABSTRACT
This article presents a method for detecting duplicate sequences in a continuous television stream. This is of interest to many applications, including commercials monitoring and video indexing. Repetitions can also be used as a way of structuring television streams by detecting inter-program breaks as a set of duplicate sequences. In this context, we present a shot-based method for detecting repeated sequences efficiently. Experiments show that this fast shot matching strategy allows us to retrieve duplicated shots between a 1 hour long query and a 24 hours database in only 10 ms.

ABSTRACT

In this paper, we propose a new method to search different instances of a video sequence inside a long video and/or video collection. The proposed method is robust to view point and illumination changes which may occur since the sequences are captured in different times with different cameras, and to the differences in the order and the number of frames in the sequences which may occur due to editing. The algorithm does not require any query to be given for searching, and finds all repeating video sequences inside a long video in a fully automatic way. First, the frames in a video are ranked according to their similarity on the distribution of salient points and colour values. Then, a tree based approach is used to seek for the repetitions of a video sequence if there is any. Results are provided on a full length feature movie, Run Lola Run and on commercials of TRECVID 2004 news video corpus.

Other:

Data Clustering and Plate Reconition. Jyh-Shing Roger Jang（張智星）Associate Professor CS Dept., Tsing Hua University, Taiwan

Ertem Tuncel, H.F., Kenneth Rose, VQ-Index:An Index Structure for Similarity Searching in Multimedia Databases. in ACM Multimedia, ( 2002 ).

這篇著重VQ 演算，VQ為類似DCT之演算，為軸坐標轉換，轉換後再做Quantization，由於VQ data partation 並非四方型，其演算複雜度不亞於DCT.
用到一些 : k-nearest-neighbor (k-NN) query.

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