Detecting Ads in Video Streams Using Acoustic and Visual Cues.
The article provides information on various techniques developed by researchers that detect and remove advertisements in video streams in the U.S. One is the repetition-based approach developed by John M. Gauch and Abhishek Shivadas. The percentage of repeated advertisements in repetition-based appr...
| Publicado en: | Computer (00189162) Vol. 39; no. 12; pp. 135 - 138 |
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| Autores principales: | , , |
| Formato: | Artículo |
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IEEE
Dec2006
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=23555761&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 23555761 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00189162 PUT jtl: Computer (00189162) issn: 00189162 maglogo: N pubinfo: dt: Dec2006 vid: 39 iid: 12 pid: 13605 pub: IEEE artinfo: ui: 23555761 10.1109/MC.2006.421 ppf: 135 ppct: 3 formats: tig: atl: Detecting Ads in Video Streams Using Acoustic and Visual Cues. aug: au: Covell, Michele Baluja, Shumeet Fink, Michael affil: Staff Research Scientist, Google Research Senior Staff Research Scientist, Google Research Student, Interdisciplinary Center for Neural Computation, the Hebrew University of Jerusalem su: Computer programming Systems development Streaming technology Advertising Sound Gauch, John M. Architectural acoustics Shivadas, Abhishek United States sug: subj: United States Computer programming Systems development Streaming technology Advertising Sound Gauch, John M. Architectural acoustics Shivadas, Abhishek ab: The article provides information on various techniques developed by researchers that detect and remove advertisements in video streams in the U.S. One is the repetition-based approach developed by John M. Gauch and Abhishek Shivadas. The percentage of repeated advertisements in repetition-based approach grows with the size of the video collection. In line with this work, a technique that use acoustic as well as visual cues to find efficiently and segment repeated material within a large collection of monitored video streams is developed. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2006 holdings: @attributes: islocal: N |
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