A novel IPTV framework for automatic TV commercials detection, labeling, recognition and replacement
dc.authorid | Arsan, Taner/0000-0002-4453-3218 | |
dc.authorwosid | Arsan, Taner/AAB-2736-2019 | |
dc.contributor.author | Arsan, Taner | |
dc.contributor.author | Bulut, Enes Emre | |
dc.contributor.author | Eren, Berk | |
dc.contributor.author | Uzgor, Ahmet | |
dc.contributor.author | Yolcu, Selcuk | |
dc.date.accessioned | 2023-10-19T15:12:39Z | |
dc.date.available | 2023-10-19T15:12:39Z | |
dc.date.issued | 2023 | |
dc.department-temp | [Arsan, Taner] Kadir Has Univ, Comp Engn Dept, TR-34083 Istanbul, Turkey; [Bulut, Enes Emre; Eren, Berk; Uzgor, Ahmet; Yolcu, Selcuk] Turcom Technol, TR-34485 Istanbul, Turkey | en_US |
dc.description.abstract | Advertisements are one of the most important way for companies to access their customers. In this context, televison commercials are gaining significant importance in many sectors daily, and it is crucial for companies to promote their products in the best way. This creates a big rivalry between companies. From this point of view, we have created an IPTV Framework that can automatically detect commercials of rival companies and replace them with desired commercials for companies to help them highlight their products to their customers. We have benefited from monochrome frames to detect the Livestream commercial block and proposed a fingerprint algorithm to create an automatic commercial database. We can easily recognize the commercials, and we can mask the commercials of rival companies with these techniques. We have tested our algorithm in real-time by streaming a recorded broadcast from a server of a specific TV channel. Experimental results show that our algorithm provides high accuracy in real-time commercial recognition. | en_US |
dc.description.sponsorship | Scientific and Technological Research Council of Turkey (TuBTAK) [7160967] | en_US |
dc.description.sponsorship | This project was financially supported by the Scientific and Technological Research Council of Turkey (TuBTAK). The Project Grant Number is 7160967. | en_US |
dc.identifier.citation | 0 | |
dc.identifier.doi | 10.1007/s11042-021-11563-y | en_US |
dc.identifier.endpage | 8579 | en_US |
dc.identifier.issn | 1380-7501 | |
dc.identifier.issn | 1573-7721 | |
dc.identifier.issue | 6 | en_US |
dc.identifier.scopus | 2-s2.0-85137210151 | en_US |
dc.identifier.scopusquality | Q1 | |
dc.identifier.startpage | 8561 | en_US |
dc.identifier.uri | https://doi.org/10.1007/s11042-021-11563-y | |
dc.identifier.uri | https://hdl.handle.net/20.500.12469/5499 | |
dc.identifier.volume | 82 | en_US |
dc.identifier.wos | WOS:000847985800003 | en_US |
dc.identifier.wosquality | N/A | |
dc.institutionauthor | Arsan, Taner | |
dc.khas | 20231019-WoS | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartof | Multimedia Tools and Applications | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Commercial detection and recognition | en_US |
dc.subject | IPTV | en_US |
dc.subject | Segmentation | En_Us |
dc.subject | Live broadcasting | en_US |
dc.subject | Video streaming | en_US |
dc.subject | Segmentation | |
dc.subject | Commercial replacing | en_US |
dc.title | A novel IPTV framework for automatic TV commercials detection, labeling, recognition and replacement | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 7959ea6c-1b30-4fa0-9c40-6311259c0914 | |
relation.isAuthorOfPublication.latestForDiscovery | 7959ea6c-1b30-4fa0-9c40-6311259c0914 |
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