Content-Based Copy Detection (CBCD) of digital videos is an important research field that aims at the identification of modified copies of an original clip, e.g., on the Internet. In this application, the video content is uniquely identified by the content itself, by extracting some compact features that are robust to a certain set of video transformations. Given the huge amount of data present in online video databases, the computational complexity of the feature extraction and comparison is a very important issue. In this paper, a landmark based multi-dimensional scaling technique is proposed to speed up the detection procedure which is based on exhaustive search and the MPEG-7 Dominant Color Descriptor. The method is evaluated under the MPEG Video Signature Core Experiment conditions, and simulation results show impressive time savings at the cost of a slightly reduced detection performance.

CBCD Based on Color Features and Landmark MDS-Assisted Distance Estimation

CORVAGLIA, Marzia
Methodology
;
GUERRINI, Fabrizio
Methodology
;
LEONARDI, Riccardo
Supervision
;
MIGLIORATI, Pierangelo
Supervision
;
ROSSI, Eliana
Membro del Collaboration Group
2010-01-01

Abstract

Content-Based Copy Detection (CBCD) of digital videos is an important research field that aims at the identification of modified copies of an original clip, e.g., on the Internet. In this application, the video content is uniquely identified by the content itself, by extracting some compact features that are robust to a certain set of video transformations. Given the huge amount of data present in online video databases, the computational complexity of the feature extraction and comparison is a very important issue. In this paper, a landmark based multi-dimensional scaling technique is proposed to speed up the detection procedure which is based on exhaustive search and the MPEG-7 Dominant Color Descriptor. The method is evaluated under the MPEG Video Signature Core Experiment conditions, and simulation results show impressive time savings at the cost of a slightly reduced detection performance.
2010
Proceedings of the 2010 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)
Ateneo di appartenenza
PE6_11 Machine learning, statistical data processing and applications using signal processing (eg. speech, image, video)
Esperti anonimi
Inglese
no
2010 International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)
Mar. 2010
Dallas, TX
Internazionale
UNICO
2374
2377
4
9781424442959
9781424442966
IEEE
ISSN 1520-6149
Content Based Copy Detection; Fingerprinting; Landmark MDS
no
partially_open
Corvaglia, Marzia; Guerrini, Fabrizio; Leonardi, Riccardo; Migliorati, Pierangelo; Rossi, Eliana
273
info:eu-repo/semantics/conferenceObject
5
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/34488
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