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Content identification using video tomography

Video identification or copy detection is a challenging problem and is becoming increasingly important with the popularity of online video services. The problem addressed in this thesis is the identification of a given video clip in a given set of videos. For a given query video, the system returns all the instance of the video in the data set. This identification system uses video signatures based on video tomography. A robust and low complexity video signature is designed and implemented. The nature of the signature makes it independent to the most commonly video transformations. The signatures are generated for video shots and not individual frames, resulting in a compact signature of 64 bytes per video shot. The signatures are matched using simple Euclidean distance metric. The results show that videos can be identified with 100% recall and over 93% precision. The experiments included several transformations on videos. / by Gustavo A. Leon. / Thesis (M.S.C.S.)--Florida Atlantic University, 2008. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2008. Mode of access: World Wide Web.

Identiferoai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_3542
ContributorsLeon, Gustavo A., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
PublisherFlorida Atlantic University
Source SetsFlorida Atlantic University
LanguageEnglish
Detected LanguageEnglish
TypeText, Electronic Thesis or Dissertation
Formatvi, 61 p. : ill. (some col.), electronic
Rightshttp://rightsstatements.org/vocab/InC/1.0/

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