Content-based video database retrieval through robust corner tracking

F. Mokhtarian, F. Mohanna
{"title":"Content-based video database retrieval through robust corner tracking","authors":"F. Mokhtarian, F. Mohanna","doi":"10.1109/MMSP.2002.1203287","DOIUrl":null,"url":null,"abstract":"A content-based video retrieval system based on extracting corners from frames and tracking them through video databases is proposed. To extract corners from each frame of video sequence in pre-processing stage, proposed multi-scale corner detector is applied. As a user interface, a proposed fast active contour model has been used to specify one object of interest as a query in one of the frames of each video shot. This frame which is in the selected-frame are extracted and tracked forwardly and backwardly through the whole of that shot using proposed multiple-match tracker. The multi-match tracker, which does not make any important assumptions or use any motion models, can retrieve the query in any video sequence even when there is unconstrained and non-smooth motion. By tracking the corners or query object forwardly and backwardly, the positions of similar objects in each video frame are determined. Two methods are considered for demonstrating the query and its similar objects to the user. Experiments have been carried out on a wide range of real video databases. All the results confirm that among the existing techniques, proposed method which exploits image corners is believed to be more generally applicable.","PeriodicalId":398813,"journal":{"name":"2002 IEEE Workshop on Multimedia Signal Processing.","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2002 IEEE Workshop on Multimedia Signal Processing.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2002.1203287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

A content-based video retrieval system based on extracting corners from frames and tracking them through video databases is proposed. To extract corners from each frame of video sequence in pre-processing stage, proposed multi-scale corner detector is applied. As a user interface, a proposed fast active contour model has been used to specify one object of interest as a query in one of the frames of each video shot. This frame which is in the selected-frame are extracted and tracked forwardly and backwardly through the whole of that shot using proposed multiple-match tracker. The multi-match tracker, which does not make any important assumptions or use any motion models, can retrieve the query in any video sequence even when there is unconstrained and non-smooth motion. By tracking the corners or query object forwardly and backwardly, the positions of similar objects in each video frame are determined. Two methods are considered for demonstrating the query and its similar objects to the user. Experiments have been carried out on a wide range of real video databases. All the results confirm that among the existing techniques, proposed method which exploits image corners is believed to be more generally applicable.
基于内容的鲁棒角点跟踪视频数据库检索
提出了一种基于帧角提取和视频数据库跟踪的基于内容的视频检索系统。为了在预处理阶段从视频序列的每一帧中提取角点,提出了一种多尺度角点检测器。作为用户界面,提出了一种快速活动轮廓模型,用于在每个视频镜头的一个帧中指定一个感兴趣的对象作为查询。利用所提出的多匹配跟踪器对选中帧中的帧进行提取,并在整个镜头中前后跟踪。多匹配跟踪器不做任何重要的假设,也不使用任何运动模型,可以在任何视频序列中检索查询,即使存在无约束和非光滑运动。通过前后跟踪角点或查询对象,确定每个视频帧中相似对象的位置。考虑使用两种方法向用户演示查询及其类似对象。在大量的真实视频数据库上进行了实验。结果表明,在现有的方法中,利用图像角点的方法具有更广泛的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信