Publication: Semantic sketch-based video retrieval with autocompletion
dc.contributor.coauthor | Tǎnase, Claudiu | |
dc.contributor.coauthor | Giangreco, Ivan | |
dc.contributor.coauthor | Rossetto, Luca | |
dc.contributor.coauthor | Schuldt, Heiko | |
dc.contributor.coauthor | Seddati, Omar | |
dc.contributor.coauthor | Dupont, Stéphane | |
dc.contributor.department | N/A | |
dc.contributor.department | Department of Computer Engineering | |
dc.contributor.kuauthor | Altıok, Ozan Can | |
dc.contributor.kuauthor | Sezgin, Tevfik Metin | |
dc.contributor.kuprofile | Master Student | |
dc.contributor.kuprofile | Faculty Member | |
dc.contributor.other | Department of Computer Engineering | |
dc.contributor.schoolcollegeinstitute | Graduate School of Sciences and Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.yokid | N/A | |
dc.contributor.yokid | 18632 | |
dc.date.accessioned | 2024-11-09T23:04:45Z | |
dc.date.issued | 2016 | |
dc.description.abstract | The 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.indexedby | Scopus | |
dc.description.openaccess | YES | |
dc.description.publisherscope | International | |
dc.description.sponsorship | ACM SIGAI | |
dc.description.sponsorship | ACM SIGCHI | |
dc.identifier.doi | 10.1145/2876456.2879473 | |
dc.identifier.isbn | 9781-4503-4140-0 | |
dc.identifier.link | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014150795&doi=10.1145%2f2876456.2879473&partnerID=40&md5=34c3d2ba0791878e296648294d6c75ee | |
dc.identifier.scopus | 2-s2.0-85014150795 | |
dc.identifier.uri | http://dx.doi.org/10.1145/2876456.2879473 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/8669 | |
dc.keywords | Content-based video retrieval | |
dc.keywords | Sketch interface | |
dc.language | English | |
dc.publisher | Association for Computing Machinery | |
dc.source | International Conference on Intelligent User Interfaces, Proceedings IUI | |
dc.subject | Computer engineering | |
dc.title | Semantic sketch-based video retrieval with autocompletion | |
dc.type | Conference proceeding | |
dspace.entity.type | Publication | |
local.contributor.authorid | N/A | |
local.contributor.authorid | 0000-0002-1524-1646 | |
local.contributor.kuauthor | Altıok, Ozan Can | |
local.contributor.kuauthor | Sezgin, Tevfik Metin | |
relation.isOrgUnitOfPublication | 89352e43-bf09-4ef4-82f6-6f9d0174ebae | |
relation.isOrgUnitOfPublication.latestForDiscovery | 89352e43-bf09-4ef4-82f6-6f9d0174ebae |