Key observation selection-based effective video synopsis for camera network

Xiaobin Zhu; Jing Liu; Jinqiao Wang; Hanqing Lu

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Key observation selection-based effective video synopsis for camera network

机译：基于关键观察选择的摄像机网络有效视频概要

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摘要

Nowadays, tremendous amount of video is captured endlessly from increased numbers of video cameras distributed around the world. Since needless information is abundant in the raw videos, making video browsing and retrieval is inefficient and time consuming. Video synopsis is an effective way to browse and index such video, by producing a short video representation, while keeping the essential activities of the original video. However, video synopsis for single camera is limited in its view scope, while understanding and monitoring overall activity for large scenarios is valuable and demanding. To solve the above issues, we propose a novel video synopsis algorithm for partially overlapping camera network. Our main contributions reside in three aspects: First, our algorithm can generate video synopsis for large scenarios, which can facilitate understanding overall activities. Second, for generating overall activity, we adopt a novel unsupervised graph matching algorithm to associate trajectories across cameras. Third, a novel multiple kernel similarity is adopted in selecting key observations for eliminating content redundancy in video synopsis. We have demonstrated the effectiveness of our approach on real surveillance videos captured by our camera network.

机译：如今，越来越多的视频摄像机被分布在世界各地的越来越多的摄像机捕获。由于原始视频中包含大量不必要的信息，因此进行视频浏览和检索效率低下且耗时。视频概要是通过产生简短的视频表示，同时保留原始视频的基本活动，来浏览和索引此类视频的有效方法。然而，用于单个摄像机的视频概要在其查看范围上受到限制，而对于大型场景而言，了解和监视整体活动是有价值且要求很高的。为了解决上述问题，我们提出了一种用于部分重叠摄像机网络的新颖视频概要算法。我们的主要贡献在于三个方面：首先，我们的算法可以为大型场景生成视频概要，从而有助于理解整体活动。其次，为了生成整体活动，我们采用了一种新颖的无监督图匹配算法来关联摄像机之间的轨迹。第三，在选择关键观测值时采用了新颖的多核相似度，以消除视频概要中的内容冗余。我们已经证明了我们的方法对由我们的摄像机网络捕获的真实监控视频的有效性。

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来源
《Machine Vision and Applications》 |2014年第1期|145-157|共13页
作者
Xiaobin Zhu; Jing Liu; Jinqiao Wang; Hanqing Lu;
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作者单位

NLPR, Institute of Automation, Chinese Academic of Sciences, Beijing 100190, China;

NLPR, Institute of Automation, Chinese Academic of Sciences, Beijing 100190, China;

NLPR, Institute of Automation, Chinese Academic of Sciences, Beijing 100190, China;

NLPR, Institute of Automation, Chinese Academic of Sciences, Beijing 100190, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Video synopsis; Graph matching; Camera network; Video surveillance;

机译：视频简介图匹配;摄像头网络;视频监控;

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4. Key observation selection for effective video synopsis [C] . Zhu Xiaobin, Liu Jing, Wang Jinqiao, Proceedings of the 21st International Conference on Pattern Recognition. . 2012

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5. Systems and algorithms for automated collaborative observation using networked robotic cameras. [D] . Xu, Yiliang. 2011

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Key observation selection-based effective video synopsis for camera network

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