Loading…
Time-Constrained Keyframe Selection Technique
In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper describes a novel technique for determining keyframes that are different from each other and provide a good representation of...
Saved in:
Published in: | Multimedia tools and applications 2000-08, Vol.11 (3), p.347 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c226t-ad69ee66f497be20b0a12499d54355e663989ba11f343378f4254a872a8095ee3 |
---|---|
cites | |
container_end_page | |
container_issue | 3 |
container_start_page | 347 |
container_title | Multimedia tools and applications |
container_volume | 11 |
creator | Girgensohn, Andreas Boreczky, John |
description | In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper describes a novel technique for determining keyframes that are different from each other and provide a good representation of the whole video. We use keyframes to distinguish videos from each other, to summarize videos, and to provide access points into them. The technique can determine any number of keyframes by clustering the frames in a video and by selecting a representative frame from each cluster. Temporal constraints are used to filter out some clusters and to determine the representative frame for a cluster. Desirable visual features can be emphasized in the set of keyframes. An application for browsing a collection of videos makes use of the keyframes to support skimming and to provide visual summaries.[PUBLICATION ABSTRACT] |
doi_str_mv | 10.1023/A:1009630817712 |
format | article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_757126557</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2158591401</sourcerecordid><originalsourceid>FETCH-LOGICAL-c226t-ad69ee66f497be20b0a12499d54355e663989ba11f343378f4254a872a8095ee3</originalsourceid><addsrcrecordid>eNotj0tLw0AUhQdRsLau3Qb3o_fOe9yV4AsLLhrXZZLcwZR2opl04b93QFfnwIHz8TF2g3CHIOT9-gEBvJHg0FoUZ2yB2kpurcDz0qUDbjXgJbvKeQ-ARgu1YLwZjsTrMeV5CkOivnqjnziFI1VbOlA3D2OqGuo-0_B9ohW7iOGQ6fo_l-zj6bGpX_jm_fm1Xm94J4SZeeiNJzImKm9bEtBCQKG877WSWpdBeufbgBilktK6qIRWwVkRHHhNJJfs9u_3axoLNs-7_XiaUkHurC5yRhe1X-IsQsw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>757126557</pqid></control><display><type>article</type><title>Time-Constrained Keyframe Selection Technique</title><source>ABI/INFORM Global</source><source>Springer Nature</source><creator>Girgensohn, Andreas ; Boreczky, John</creator><creatorcontrib>Girgensohn, Andreas ; Boreczky, John</creatorcontrib><description>In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper describes a novel technique for determining keyframes that are different from each other and provide a good representation of the whole video. We use keyframes to distinguish videos from each other, to summarize videos, and to provide access points into them. The technique can determine any number of keyframes by clustering the frames in a video and by selecting a representative frame from each cluster. Temporal constraints are used to filter out some clusters and to determine the representative frame for a cluster. Desirable visual features can be emphasized in the set of keyframes. An application for browsing a collection of videos makes use of the keyframes to support skimming and to provide visual summaries.[PUBLICATION ABSTRACT]</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1023/A:1009630817712</identifier><language>eng</language><publisher>Dordrecht: Springer Nature B.V</publisher><subject>Digital libraries ; Studies ; Video</subject><ispartof>Multimedia tools and applications, 2000-08, Vol.11 (3), p.347</ispartof><rights>Kluwer Academic Publishers 2000</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c226t-ad69ee66f497be20b0a12499d54355e663989ba11f343378f4254a872a8095ee3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/757126557/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/757126557?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11688,27924,27925,36060,44363,74895</link.rule.ids></links><search><creatorcontrib>Girgensohn, Andreas</creatorcontrib><creatorcontrib>Boreczky, John</creatorcontrib><title>Time-Constrained Keyframe Selection Technique</title><title>Multimedia tools and applications</title><description>In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper describes a novel technique for determining keyframes that are different from each other and provide a good representation of the whole video. We use keyframes to distinguish videos from each other, to summarize videos, and to provide access points into them. The technique can determine any number of keyframes by clustering the frames in a video and by selecting a representative frame from each cluster. Temporal constraints are used to filter out some clusters and to determine the representative frame for a cluster. Desirable visual features can be emphasized in the set of keyframes. An application for browsing a collection of videos makes use of the keyframes to support skimming and to provide visual summaries.[PUBLICATION ABSTRACT]</description><subject>Digital libraries</subject><subject>Studies</subject><subject>Video</subject><issn>1380-7501</issn><issn>1573-7721</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2000</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNotj0tLw0AUhQdRsLau3Qb3o_fOe9yV4AsLLhrXZZLcwZR2opl04b93QFfnwIHz8TF2g3CHIOT9-gEBvJHg0FoUZ2yB2kpurcDz0qUDbjXgJbvKeQ-ARgu1YLwZjsTrMeV5CkOivnqjnziFI1VbOlA3D2OqGuo-0_B9ohW7iOGQ6fo_l-zj6bGpX_jm_fm1Xm94J4SZeeiNJzImKm9bEtBCQKG877WSWpdBeufbgBilktK6qIRWwVkRHHhNJJfs9u_3axoLNs-7_XiaUkHurC5yRhe1X-IsQsw</recordid><startdate>20000801</startdate><enddate>20000801</enddate><creator>Girgensohn, Andreas</creator><creator>Boreczky, John</creator><general>Springer Nature B.V</general><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20000801</creationdate><title>Time-Constrained Keyframe Selection Technique</title><author>Girgensohn, Andreas ; Boreczky, John</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c226t-ad69ee66f497be20b0a12499d54355e663989ba11f343378f4254a872a8095ee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Digital libraries</topic><topic>Studies</topic><topic>Video</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Girgensohn, Andreas</creatorcontrib><creatorcontrib>Boreczky, John</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer science database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>ProQuest research library</collection><collection>Research Library (Corporate)</collection><collection>ProQuest advanced technologies & aerospace journals</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Multimedia tools and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Girgensohn, Andreas</au><au>Boreczky, John</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Time-Constrained Keyframe Selection Technique</atitle><jtitle>Multimedia tools and applications</jtitle><date>2000-08-01</date><risdate>2000</risdate><volume>11</volume><issue>3</issue><spage>347</spage><pages>347-</pages><issn>1380-7501</issn><eissn>1573-7721</eissn><abstract>In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper describes a novel technique for determining keyframes that are different from each other and provide a good representation of the whole video. We use keyframes to distinguish videos from each other, to summarize videos, and to provide access points into them. The technique can determine any number of keyframes by clustering the frames in a video and by selecting a representative frame from each cluster. Temporal constraints are used to filter out some clusters and to determine the representative frame for a cluster. Desirable visual features can be emphasized in the set of keyframes. An application for browsing a collection of videos makes use of the keyframes to support skimming and to provide visual summaries.[PUBLICATION ABSTRACT]</abstract><cop>Dordrecht</cop><pub>Springer Nature B.V</pub><doi>10.1023/A:1009630817712</doi></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1380-7501 |
ispartof | Multimedia tools and applications, 2000-08, Vol.11 (3), p.347 |
issn | 1380-7501 1573-7721 |
language | eng |
recordid | cdi_proquest_journals_757126557 |
source | ABI/INFORM Global; Springer Nature |
subjects | Digital libraries Studies Video |
title | Time-Constrained Keyframe Selection Technique |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T08%3A54%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Time-Constrained%20Keyframe%20Selection%20Technique&rft.jtitle=Multimedia%20tools%20and%20applications&rft.au=Girgensohn,%20Andreas&rft.date=2000-08-01&rft.volume=11&rft.issue=3&rft.spage=347&rft.pages=347-&rft.issn=1380-7501&rft.eissn=1573-7721&rft_id=info:doi/10.1023/A:1009630817712&rft_dat=%3Cproquest%3E2158591401%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c226t-ad69ee66f497be20b0a12499d54355e663989ba11f343378f4254a872a8095ee3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=757126557&rft_id=info:pmid/&rfr_iscdi=true |