基于相似值分解和潜在语义索引的视频检索

K. Thakare, R. Manthalkar, A. Rajurkar, D. Deshapande
{"title":"基于相似值分解和潜在语义索引的视频检索","authors":"K. Thakare, R. Manthalkar, A. Rajurkar, D. Deshapande","doi":"10.1109/ICCICT.2012.6398229","DOIUrl":null,"url":null,"abstract":"Similarity matching algorithm plays an important role in Video retrieval system. Most of the video retrieval systems are designed using traditional similarity matching algorithms that are based on distance measures. As the Accuracy of retrieval system depends on the method used for detecting shots, kind of features we use for retrieval, it is also mandatory to think about the algorithms that we use for similarity matching of video clips. Here we propose a new technique latent semantic indexing technique which is based on Singular value decomposition. A key feature of LSI is its ability to establish associations between similar kind of information, It easily provides the accurate index terms that matches with the query clip index. We compare the results obtained with results of traditional Euclidean Distance method. Results are satisfactory.","PeriodicalId":319467,"journal":{"name":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Video retrieval using singilar value decomposition and latent semantic indexing\",\"authors\":\"K. Thakare, R. Manthalkar, A. Rajurkar, D. Deshapande\",\"doi\":\"10.1109/ICCICT.2012.6398229\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Similarity matching algorithm plays an important role in Video retrieval system. Most of the video retrieval systems are designed using traditional similarity matching algorithms that are based on distance measures. As the Accuracy of retrieval system depends on the method used for detecting shots, kind of features we use for retrieval, it is also mandatory to think about the algorithms that we use for similarity matching of video clips. Here we propose a new technique latent semantic indexing technique which is based on Singular value decomposition. A key feature of LSI is its ability to establish associations between similar kind of information, It easily provides the accurate index terms that matches with the query clip index. We compare the results obtained with results of traditional Euclidean Distance method. Results are satisfactory.\",\"PeriodicalId\":319467,\"journal\":{\"name\":\"2012 International Conference on Communication, Information & Computing Technology (ICCICT)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Communication, Information & Computing Technology (ICCICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCICT.2012.6398229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Communication, Information & Computing Technology (ICCICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCICT.2012.6398229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

相似匹配算法在视频检索系统中起着重要的作用。大多数视频检索系统都是使用传统的基于距离度量的相似匹配算法设计的。由于检索系统的准确性取决于我们用来检测镜头的方法,我们用来检索的特征,我们也必须考虑我们用来匹配视频片段的相似度的算法。本文提出了一种基于奇异值分解的潜在语义索引技术。大规模集成电路的一个关键特点是它能够在相似类型的信息之间建立关联,它很容易提供与查询片段索引匹配的准确索引项。我们将得到的结果与传统的欧几里得距离法的结果进行了比较。结果令人满意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Video retrieval using singilar value decomposition and latent semantic indexing
Similarity matching algorithm plays an important role in Video retrieval system. Most of the video retrieval systems are designed using traditional similarity matching algorithms that are based on distance measures. As the Accuracy of retrieval system depends on the method used for detecting shots, kind of features we use for retrieval, it is also mandatory to think about the algorithms that we use for similarity matching of video clips. Here we propose a new technique latent semantic indexing technique which is based on Singular value decomposition. A key feature of LSI is its ability to establish associations between similar kind of information, It easily provides the accurate index terms that matches with the query clip index. We compare the results obtained with results of traditional Euclidean Distance method. Results are satisfactory.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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