Multimedia copy detection
department or school: Applied Science, Faculty of
department or school: Electrical and Computer Engineering, Department of
data provider: DSpace
degree campus: UBCV
creator: Malek Esmaeili, Mani
issued: 2013-06-22T09:20:36Z
issued: 2013
related degree: Doctor of Philosophy - PhD
degree grantor: University of British Columbia
description: Asmultimedia-sharing websites are becoming increasingly popular, content providers get more concerned about the illegal distribution of their copyrighted contents. The recent content-based multimedia fingerprinting technology has evolved as an important tool for automatically detecting illegal copies of audio, image, and video signals. Multimedia fingerprints are signatures that are extracted from an audio, image, or video signal as a compact identifier of the signal. Therefore fingerprints should have enough discriminating ability to identify a multimedia object among others. At the same time they should be robust to modifications a multimedia signal might be subjected, such as compression, cropping, format change, scaling, and other signal processing operations. Robustness requires the fingerprints of a signal to only depend on the signals perceptual content and not on its format, size, quality, etc. This thesis proposes copy detection systems for audio and video signals and addresses the robustness as well as the discrimination ability of these systems. We first address audio fingerprinting and propose an algorithm that can detect small snippets of audio signals. Simulation results show that, the extracted fingerprints are robust to audio modifications including pitch shift and tempo change. For severe modifications that existing algorithms have poor detection rates (around 20%), our proposed algorithm yields detection rates above 80%. We then address video fingerprinting and propose an algorithm that extracts robust and discriminant binary fingerprints. Simulation results show that the proposed algorithm is faster and more accurate than the state-of-the-art with a high true positive rate of over 97% and a low false positive rate below 1%. Another challenge in multimedia fingerprinting is fingerprint retrieval, i.e. searching a huge fingerprint database (millions of fingerprints), for an accurate match for a query fingerprint in a fast fashion. We propose a fast …
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/44581
note: Multimedia copy detection by Mani Malek Esmaeili B.Sc., University of Tehran, 2004 M.Sc., University of Tehran, 2007 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Doctor of Philosophy in THE FACULTY OF GRADUATE STUDIES (Electrical and Computer Engineering) The University of British Columbia (Vancouver) June 2013 c© Mani Malek Esmaeili, 2013 Abstract As multimedia-sharing websites are becoming increasingly popular, content providers get more concerned about the illegal distribution of their copyrighted contents. The recent content-based multimedia fingerprinting technology has evolved as an im- portant tool for automatically detecting illegal copies of audio, image, and video signals. Multimedia fingerprints are signatures that are extracted from an audio, image, or video signal as a compact identifier of the signal. Therefore fingerprints should have enough discriminating ability to identify a multimedia object among others. At the same time they should be robust to modifications a multimedia signal might be subjected, such as compression, cropping, format change, scaling, and other signal processing operations. Robustness requires the fingerprints of a signal to only depend on the signals perceptual content and not on its format, size, quality, etc. This thesis proposes copy detection systems for audio and video signals and addresses the robustness as well as the discrimination ability of these systems. We first address audio fingerprinting and propose an algorithm that can detect small snippets of audio signals. Simulation results show that, the extracted finger- prints are robust to audio modifications including pitch shift and tempo change. For severe modifications that existing algorithms have poor detection rates (around 20%), our proposed algorithm yields detection rates above 80%. We then address video fingerprinting and propose an algorithm that extracts robust and discriminant binary fingerprints. Simulation results show t…
has type: Thesis/Dissertation
date issued: 2013-11
is shown at: 10.14288/1.0073906
language: eng
degree discipline: Electrical and Computer Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivs 3.0 Unported
rights URI: http://creativecommons.org/licenses/by-nc-nd/3.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/44581