Publication:
Semantic sketch-based video retrieval with autocompletion

dc.contributor.coauthorTǎnase, Claudiu
dc.contributor.coauthorGiangreco, Ivan
dc.contributor.coauthorRossetto, Luca
dc.contributor.coauthorSchuldt, Heiko
dc.contributor.coauthorSeddati, Omar
dc.contributor.coauthorDupont, Stéphane
dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.kuauthorAltıok, Ozan Can
dc.contributor.kuauthorSezgin, Tevfik Metin
dc.contributor.kuprofileMaster Student
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Computer Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid18632
dc.date.accessioned2024-11-09T23:04:45Z
dc.date.issued2016
dc.description.abstractThe IMOTION system is a content-based video search engine that provides fast and intuitive known item search in large video collections. User interaction consists mainly of sketching, which the system recognizes in real-time and makes suggestions based on both visual appearance of the sketch (what does the sketch look like in terms of colors, edge distribution, etc.) and semantic content (what object is the user sketching). The latter is enabled by a predictive sketch-based UI that identifies likely candidates for the sketched object via state-of-the-art sketch recognition techniques and offers on-screen completion suggestions. In this demo, we show how the sketch-based video retrieval of the IMOTION system is used in a collection of roughly 30,000 video shots. The system indexes collection data with over 30 visual features describing color, edge, motion, and semantic information. Resulting feature data is stored in ADAM, an efficient database system optimized for fast retrieval.
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsorshipACM SIGAI
dc.description.sponsorshipACM SIGCHI
dc.identifier.doi10.1145/2876456.2879473
dc.identifier.isbn9781-4503-4140-0
dc.identifier.linkhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85014150795&doi=10.1145%2f2876456.2879473&partnerID=40&md5=34c3d2ba0791878e296648294d6c75ee
dc.identifier.scopus2-s2.0-85014150795
dc.identifier.urihttp://dx.doi.org/10.1145/2876456.2879473
dc.identifier.urihttps://hdl.handle.net/20.500.14288/8669
dc.keywordsContent-based video retrieval
dc.keywordsSketch interface
dc.languageEnglish
dc.publisherAssociation for Computing Machinery
dc.sourceInternational Conference on Intelligent User Interfaces, Proceedings IUI
dc.subjectComputer engineering
dc.titleSemantic sketch-based video retrieval with autocompletion
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.authorid0000-0002-1524-1646
local.contributor.kuauthorAltıok, Ozan Can
local.contributor.kuauthorSezgin, Tevfik Metin
relation.isOrgUnitOfPublication89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae

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