Surveillance Video Synopsis via Scaling Down Objects | |
Li, Xuelong1; Wang, Zhigang2,3; Lu, Xiaoqiang1 | |
作者部门 | 光学影像学习与分析中心 |
2016-02-01 | |
发表期刊 | IEEE TRANSACTIONS ON IMAGE PROCESSING |
ISSN | 1057-7149 |
卷号 | 25期号:2页码:740-755 |
产权排序 | 1 |
摘要 | Video synopsis is an effective technique to provide a compact representation of the original video by removing spatiotemporal redundancies and by preserving the essential activities. Most current approaches for video synopsis will cause collisions among objects, especially when the video is condensed much. In this paper, we present an approach for video synopsis to reduce the collisions. Our approach first shifts active objects along the time axis to compact the original video. Then, the sizes of the objects are reduced when collisions occur. Meanwhile, the geometric centroids of the objects will be kept unchanged to preserve the location information. Our contributions are threefold. First, an approach is proposed to decrease collisions in the synopsis video through reducing the sizes of the objects. Second, an optimization framework is developed to indicate the optimal time position and the appropriate reduction coefficient for each object. Finally, some metrics are proposed, and several experiments are carried out to evaluate the proposed approach. The experiments have demonstrated that the synopsis video produced by our approach has much fewer collisions while the compression ratio is high. |
文章类型 | Article |
关键词 | Video Synopsis Surveillance Reduce Collision Reduce Size Optimization |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1109/TIP.2015.2507942 |
收录类别 | SCI ; EI |
关键词[WOS] | GRAPH CUTS ; MODEL ; OPTIMIZATION ; ATTENTION ; IMAGES |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering |
项目资助者 | Fundamental Research Funds for the Central Universities(3102015BJ(II)JJZ01) ; National Basic Research Program of China (973 Program)(2012CB719905) ; National Natural Science Foundation of China(61472413) ; Key Research Program through the Chinese Academy of Sciences(KGZD-EW-T03) ; Open Research Fund of the Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences(LSIT201408) |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000383905800019 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/28247 |
专题 | 光谱成像技术研究室 |
作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China 2.Northwestern Polytech Univ, Sch Comp Sci, Xian 710072, Shaanxi, Peoples R China 3.Northwestern Polytech Univ, Ctr Opt IMagery Anal & Learning OPTIMAL, Xian 710072, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Li, Xuelong,Wang, Zhigang,Lu, Xiaoqiang. Surveillance Video Synopsis via Scaling Down Objects[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2016,25(2):740-755. |
APA | Li, Xuelong,Wang, Zhigang,&Lu, Xiaoqiang.(2016).Surveillance Video Synopsis via Scaling Down Objects.IEEE TRANSACTIONS ON IMAGE PROCESSING,25(2),740-755. |
MLA | Li, Xuelong,et al."Surveillance Video Synopsis via Scaling Down Objects".IEEE TRANSACTIONS ON IMAGE PROCESSING 25.2(2016):740-755. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Surveillance video s(4541KB) | 期刊论文 | 作者接受稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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