Maximum a Posteriori Probability Estimation for Online Surveillance Video Synopsis

被引：62

作者：

Huang, Chun-Rong ^{[1
,2
]}

Chung, Pau-Choo ^{[3
,4
]}

Yang, Di-Kai ^{[3
]}

Chen, Hsing-Cheng ^{[3
]}

Huang, Guan-Jie ^{[1
]}

机构：

[1] Natl Chung Hsing Univ, Dept Comp Sci & Engn, Taichung 402, Taiwan

[2] Natl Chung Hsing Univ, Inst Networking & Multimedia, Taichung 402, Taiwan

[3] Natl Cheng Kung Univ, Inst Comp & Commun Engn, Tainan 70101, Taiwan

[4] Natl Cheng Kung Univ, Dept Elect Engn, Tainan 70101, Taiwan

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY | 2014年 / 24卷 / 08期

关键词：

Maximum a posteriori (MAP) estimation; video summarization; video surveillance; video synopsis; SEGMENTATION; RECOGNITION; MODEL; SCALE;

D O I：

10.1109/TCSVT.2014.2308603

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

To reduce human efforts in browsing long surveillance videos, synopsis videos are proposed. Traditional synopsis video generation applying optimization on video tubes is very time consuming and infeasible for real-time online generation. This dilemma significantly reduces the feasibility of synopsis video generation in practical situations. To solve this problem, the synopsis video generation problem is formulated as a maximum a posteriori probability (MAP) estimation problem in this paper, where the positions and appearing frames of video objects are chronologically rearranged in real time without the need to know their complete trajectories. Moreover, a synopsis table is employed with MAP estimation to decide the temporal locations of the incoming foreground objects in the synopsis video without needing an optimization procedure. As a result, the computational complexity of the proposed video synopsis generation method can be significantly reduced. Furthermore, as it does not require prescreening the entire video, this approach can be applied on online streaming videos.

引用

页码：1417 / 1429

页数：13

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