Knowledge Commons of Institute of Automation，CAS
| High-Performance Video Condensation System | |
Zhu, Jianqing1,2; Feng, Shikun1; Yi, Dong1; Liao, Shengcai1 ; Lei, Zhen1; Li, Stan Z.1
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| 发表期刊 | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
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| 2015-07-01 | |
| 卷号 | 25期号:7页码:1113-1124 |
| 文章类型 | Article |
| 摘要 | Video synopsis or condensation is a smart solution for fast video browsing and storage. However, most of the existing methods work offline, where two main phases are required. The first phase is to prepare tubes and background images. The second phase is to rearrange tubes and stitch them into backgrounds. However, with a long video sequence, the first phase is memory consuming for data storage, and the second phase is computationally expensive to rearrange all tubes simultaneously. To overcome these problems, we propose a high-performance video condensation system based on an online content-aware framework. The online framework transforms the optimization problem of tube rearrangement into a stepwise optimization problem. Therefore, it can condense video with much less memory and higher speed than the offline framework. With the aid of this transformation, the proposed system can process input videos and produce condensed videos simultaneously. Thus it is suitable for real-time endless surveillance videos. Meanwhile, the online mechanism allows users to directly visit the condensation video that has been generated. Moreover, the content-aware mechanism makes the proposed system able to automatically determine the duration of a condensed video. Finally, the proposed system uses Graphic Processing Unit (GPU) and multicore techniques to improve the speed. Extensive experiments that validate the high efficiency of the system are presented. |
| 关键词 | Gpu Acceleration Moving Object Segmentation Online Background Generation Video Condensation System Video Storage Video Surveillance |
| WOS标题词 | Science & Technology ; Technology |
| 关键词[WOS] | TRACKING |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS研究方向 | Engineering |
| WOS类目 | Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000357616600003 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/8871 |
| 专题 | 多模态人工智能系统全国重点实验室_生物识别与安全技术 |
| 作者单位 | 1.Chinese Acad Sci, Natl Lab Pattern Recognit, Ctr Biometr & Secur Res, Inst Automat, Beijing 100190, Peoples R China 2.Fujian Normal Univ, Fac Software, Fuzhou 350108, Peoples R China |
| 第一作者单位 | 模式识别国家重点实验室 |
| 推荐引用方式 GB/T 7714 | Zhu, Jianqing,Feng, Shikun,Yi, Dong,et al. High-Performance Video Condensation System[J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,2015,25(7):1113-1124. |
| APA | Zhu, Jianqing,Feng, Shikun,Yi, Dong,Liao, Shengcai,Lei, Zhen,&Li, Stan Z..(2015).High-Performance Video Condensation System.IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,25(7),1113-1124. |
| MLA | Zhu, Jianqing,et al."High-Performance Video Condensation System".IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 25.7(2015):1113-1124. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Zhu-TCSVT-2015.pdf（3439KB） | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 | |
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