[1]叶 鸥,李占利.视频数据质量与视频数据检测技术[J].西安科技大学学报,2017,(06):919-926.[doi:10.13800/j.cnki.xakjdxxb.2017.0623 ]
 YE Ou,LI Zhan-li.Video quality and video data detection technology[J].Journal of Xi'an University of Science and Technology,2017,(06):919-926.[doi:10.13800/j.cnki.xakjdxxb.2017.0623 ]
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视频数据质量与视频数据检测技术(/HTML)
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西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

卷:
期数:
2017年06期
页码:
919-926
栏目:
出版日期:
2017-11-30

文章信息/Info

Title:
Video quality and video data detection technology
文章编号:
1672-9315(2017)06-0919-08
作者:
叶 鸥李占利
西安科技大学 计算机科学与技术学院,陕西 西安 710054
Author(s):
YE OuLI Zhan-li
(College of Computer Science and Engineering,Xi'an University of Science and Technology,Xi'an 710054,China)
关键词:
视频数据质量 视频检测 脏数据 相似重复视频数据 异常视频数据
Keywords:
video data quality video detection dirty data near-duplicate video abnormal video
分类号:
TP 391.41
DOI:
10.13800/j.cnki.xakjdxxb.2017.0623
文献标志码:
A
摘要:
视频检测技术有助于改善视频数据质量问题。随着科技进步和信息技术发展,视频数据规模急剧增加,视频数据质量问题越来越受到人们关注。针对相似重复视频数据和异常视频数据这2类脏视频数据的检测技术将有助于发现并解决视频数据质量问题。为此,通过扩展视频数据质量概念,针对这2类脏视频数据,分析和总结相关的视频检测方法及关键技术; 最后,简要说明视频检测技术研究的不足,并对视频检测技术的应用进行了总结和展望。
Abstract:
Video detection technology can benefit to improving video data quality.With technological advancement and information technology development,the scale of video data is growing rapidly,and the issue of video data quality is paid more and more attention.For near-duplicate and abnormal video data,the detection technologies of these two types of dirty data will contribute to find and solve the problem of video data quality.For this purpose,by extending the concept of video data quality,we analyzed and summarized the video detection methods and key technologies for these two types of dirty video data.Finally,the defects of video detection technology were pointed out,and the future research topics and application of video detection technology have been discussed.

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备注/Memo

备注/Memo:
收稿日期:2017-06-10 责任编辑:李克永
基金项目:国家自然科学基金(煤炭联合基金)(U1261114); 陕西省教育厅专项科学研究项目(16JK1505); 陕西省自然科学基础研究计划面上项目(2017JM6105)
通讯作者:叶鸥(1984-),男,陕西咸阳人,博士,讲师,E-mail:oye0928@xust.edu.cn
更新日期/Last Update: 2017-12-11