Unsupervised, efficient and scalable key-frame selection for automatic summarization of surveillance videos

Unsupervised, efficient and scalable key-frame selection for automatic summarization of surveillance videos
复制标题

无监督、高效且可扩展的关键帧选择,用于自动总结监控视频

DOI:
10.1007/s11042-016-3263-z
复制
发表时间:
2017-03
影响因子:
3.6
通讯作者:
Yan Peng
Yan Peng
中科院分区:
计算机科学4区
文献类型:
--
作者:
Lu Guoliang;Zhou Yiqi;Li Xueyong;Yan Peng

文献摘要

参考文献

被引文献

相似文献

近年来,在公共场所部署基于视觉的监控的数量急剧增长。因此,监控视频的自动摘要(ASOSV)在许多实际应用中变得越来越受欢迎。为此,本文提出了一种新的帧选择框架,它具有三个特性:1)非监督:它可以在不需要任何监督学习或训练的情况下工作; 2)效率:它可以非常快速地工作,实验证明效率比实时性更快; 3)可扩展性:它可以实现视频内容的分层分析/概述。系统地评估了所提出的框架的性能,并与各种最先进的帧选择技术在一些收集的视频序列和公开的ViSOR数据集进行了比较。实验结果表明,有前途的性能和良好的适用性,为现实世界的问题。
Recent years have witnessed a dramatical growth of the deployment of vision-based surveillance in public spaces. Automatic summarization of surveillance videos (ASOSV) is hence becoming more and more desirable in many real-world applications. For this purpose, a novel frame-selection framework is proposed in the present paper, which has three properties: 1)un-supervision:it can work without requirements of any supervised learning or training; 2)efficiency:it can work very fast, with experiments demonstrating efficiency faster than real-timeness and 3)scalability:it can achieve a hierarchical analysis/overview of video content. The performance of proposed framework is systematically evaluated and compared with various state-of-the-art frame selection techniques on some collected video sequences and publicly-availableViSORdataset. The experimental results demonstrate promising performance and good applicability for real-world problems.
DOI: --
发表时间: 2005-12
期刊: --
影响因子: --
作者:
Z. Xiong;R. Radhakrishnan;Ajay Divakaran;Y. Rui;Thomas S. Huang
通讯作者: Z. Xiong;R. Radhakrishnan;Ajay Divakaran;Y. Rui;Thomas S. Huang
DOI: 10.1109/tkde.2013.114
发表时间: 2014-05
影响因子: 8.9
作者:
Xin Zhang;F. Sun;Guangcan Liu;Yi Ma
通讯作者: Xin Zhang;F. Sun;Guangcan Liu;Yi Ma
DOI: 10.1007/s00799-005-0129-9
发表时间: 2006-04
影响因子: 1.5
作者:
P. Mundur;Yong Rao;Y. Yesha
通讯作者: P. Mundur;Yong Rao;Y. Yesha
DOI: 10.1007/s11042-009-0402-9
发表时间: 2010-11
影响因子: 3.6
作者:
R. Vezzani;R. Cucchiara
通讯作者: R. Vezzani;R. Cucchiara
DOI: 10.1016/b978-012369387-7/50009-5
发表时间: 2006
期刊: --
影响因子: --
作者:
Z. Xiong;R. Radhakrishnan;Ajay Divakaran;Y. Rui;Thomas S. Huang
通讯作者: Z. Xiong;R. Radhakrishnan;Ajay Divakaran;Y. Rui;Thomas S. Huang