Video copy detection based on spatiotemporal fusion model

被引：0

作者：

Li, Jianmin ^{[1
]}

Liang, Yingyu ^{[1
]}

Zhang, Bo ^{[1
]}

机构：

[1] Department of Computer Science and Technology, Tsinghua National Laboratory for Information Science and Technology (TNList), Tsinghua University

来源：

Tsinghua Science and Technology | 2012年 / 17卷 / 01期

关键词：

probabilistic graphical model; spatiotemporal fusion model; video copy detection;

D O I：

10.1109/TST.2012.6151907

中图分类号：

学科分类号：

摘要：

Content-based video copy detection is an active research field due to the need for copyright protection and business intellectual property protection. This paper gives a probabilistic spatiotemporal fusion approach for video copy detection. This approach directly estimates the location of the copy segment with a probabilistic graphical model. The spatial and temporal consistency of the video copy is embedded in the local probability function. An effective local descriptor and a two-level descriptor pairing method are used to build a video copy detection system to evaluate the approach. Tests show that it outperforms the popular voting algorithm and the probabilistic fusion framework based on the Hidden Markov Model, improving F-score (F1) by 8%. © 2012 Tsinghua University Press.

引用

页码：51 / 59

页数：8

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