Article

Scene duplicate detection from videos based on trajectories of feature points

Authors:

Shin'ichi Satoh,

Masao Takimoto,

Jun AdachiAuthors Info & Claims

MIR '07: Proceedings of the international workshop on Workshop on multimedia information retrieval

Pages 237 - 244

https://doi.org/10.1145/1290082.1290115

Published: 24 September 2007 Publication History

Abstract

Recently near duplicate shot detection attracts researchers attention. There are several promising applications of near duplicate detection, especially when applied to broadcast video streams. However, currently studied near duplicates are limited to: a) The same video material (footage) used several times in different programs (strict near duplicate), and b) Less strict near duplicates such as footages of the same objects or the same background (object duplicate). In this paper, we propose a method to detect scene duplicates, another type of near duplicate. This type of near duplicate is composed of different footages taking the same scene, the same event, at the same time, but from the different viewpoints, e.g., by the different cameras, and possibly with temporal offsets. This type of near duplicate is particularly useful to identify the same event reported in the different programs and especially by the different broadcast stations. To handle this, we employ matching of temporal pattern of discontinuities obtained from trajectories of feature points. To detect discontinuities and to match trajectories, we used inconsistency. The method is accelerated by two-stage approach: the first stage is filtering by using temporal discontinuity patterns, and the second is precise matching by normalized cross correlation between inconsistency sequences of trajectories. The first stage is further accelerated by using interval histograms. Its performance is demonstrated with actual broadcasted videos from five channels and three hours from each channel, in total 15 hours.

References

[1]

Y. Caspi and M. Irani. Spatio-temporal alignment of sequences. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24(11), 2002.

Digital Library

[2]

S. S. Cheung and A. Zakhor. Efficient video similarity measurement and search. In Proc. of ICIP, 2000.

[3]

D. DeMenthon and D. Doermann. Video retrieval using spatio-temporal descriptors. In Proc. of ACM Multimedia, pages 508--517, 2003.

Digital Library

[4]

L.-Y. Duan, J. Wang, Y. Zheng, J. S. Jin, H. Lu, and C. Xu. Segmentation, categorization, and identification of commercial clips from TV streams using multimodal analysis. In Proc. of ACM Multimedia, pages 201--210, 2006.

Digital Library

[5]

A. Hampapur and R. M. Bolle. Comparison of distance measures for video copy detection. In Proc. of ICME, 2001.

[6]

T. C. Hoad and J. Zobel. Fast video matching with signature alignment. In Proc. of ACM SIGMM workshop on Multimedia Information Retrieval, pages 262--269, 2003.

Digital Library

[7]

W. H. Hsu and S.-F. Chang. Topic tracking across broadcast news videos with visual duplicates and semantic concepts. In Proc. of ICIP, 2006.

[8]

I. Ide, H. Mo, N. Katayama, and S. Satoh. Topic threading for structuring a large-scale news video archive. In Proc. of International Conference on Image and Video Retrieval (CIVR2004), pages 123--131, 2004.

[9]

K. Iwamoto, E. Kasutani, and A. Yamada. Image signature robust to caption superimposition for video sequence identification. In Proc. of International Conference on Image Processing (ICIP 2006), 2006.

[10]

A. Jaimes, S. Chang, and A. C. Loui. Duplicate detection in consumer photography and news video. In Proc. of ACM Multimedia, pages 423--424, 2002.

Digital Library

[11]

A. Joly, O. Buisson, and C. Frelicot. Content-based copy detection using distortion-based probabilistic similarity search. IEEE Transactions on Multimedia, 9(2):293--306, 2007.

Digital Library

[12]

J. Law-To, O. Buisson, V. Gouet-Brunet, and N. Boujemaa. Robust voting algorithm based on labels of behavior for video copy detection. In ACM Multimedia, 2006.

Digital Library

[13]

H. Lejsek, F. Asmundsson, B. Jónsson, and L. Amsaleg. Scalability of local descriptors: A comparative study. In ACM Multimedia, 2006.

Digital Library

[14]

D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91--110, 2004.

Digital Library

[15]

A. Nagasaka and T. Miyatake. A quick scene classification method based on compact encoding of video feature sequence. Systems and Computers in Japan, 31(1):102--108, 2000.

[16]

S. Satoh. News video analysis based on identical shot detection. In Proc. of International Conference on Multimedia and Expo, 2002.

[17]

E. Shechtman and M. Irani. Space-time behavior based correlation. In Proc. CVPR, pages 405--412, 2005.

Digital Library

[18]

M. Takimoto, S. Satoh, and M. Sakauchi. Identification and detection of the same scene based on flashlight patterns. In Proc. ICME, 2006.

[19]

C. Tomasi and T. Kanade. Detection and tracking of point features. Technical Report CMU-CS-91-132, Carnegie Mellon University, School of Computer Science, 1991.

[20]

X. Wu, A. G. Hauptmann, and C.-W. Ngo. Novelty and redundancy detection with multimodalities in cross-lingual broadcast domain. Computer Vision and Image Understanding, 2007 (to be published).

Digital Library

[21]

X. Wu, C.-W. Ngo, and Q. Li. Threading and autodocumenting news videos. IEEE Signal Processing Magazine, 23(2):59--68, March 2006.

[22]

F. Yamagishi, S. Satoh, and M. Sakauchi. A news video browser using identical video segment detection. In Proc. of Pacific-Rim Conference on Multimedia (PCM2004), volume II, pages 205--212, 2004.

Digital Library

[23]

J. Yuan, L.-Y. Duan, Q. Tian, and C. Xu. Fast and robust short video clip search using an index structure. In Proc. of ACM SIGMM international workshop on Multimedia information retrieval (MIR), pages 61--68, 2004.

Digital Library

[24]

Y. Zhai and M. Shah. Tracking news stories across different sources. In ACM Multimedia, 2005.

Digital Library

[25]

W. Zhao, C.-W. Ngo, H.-K. Tan, and X. Wu. near-duplicate keyframe retrieval and detection: Matching, filtering and learning. IEEE Transaction on Multimedia, 2007 (to appear).

Cited By

Shen LHong RHao Y(2020)Advance on large scale near-duplicate video retrievalFrontiers of Computer Science10.1007/s11704-019-8229-714:5Online publication date: 3-Jan-2020
https://doi.org/10.1007/s11704-019-8229-7
Héritier MGagnon LFoucher S(2018)Places clustering of full-length film key-framesusing latent aspect modeling over SIFT matchesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2009.201730419:6(832-841)Online publication date: 31-Dec-2018
https://dl.acm.org/doi/10.1109/TCSVT.2009.2017304
Li YChen X(2017)Robust and compact video descriptor learned by deep neural network2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2017.7952539(2162-2166)Online publication date: Mar-2017
https://doi.org/10.1109/ICASSP.2017.7952539
Show More Cited By

Index Terms

Scene duplicate detection from videos based on trajectories of feature points
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
2. Information systems
  1. Information retrieval
    1. Document representation

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Published In

cover image ACM Conferences

MIR '07: Proceedings of the international workshop on Workshop on multimedia information retrieval

September 2007

343 pages

ISBN:9781595937780

DOI:10.1145/1290082

General Chairs:
James Z. Wang
The Pennsylvania State University, USA
,
Nozha Boujemaa
INRIA Rocquencourt, France
,
Program Chairs:
Alberto Del Bimbo
University of Florence, Italy
,
Jia Li
The Pennsylvania State University, USA

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 September 2007

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MM07: The 15th ACM International Conference on Multimedia 2007

September 24 - 29, 2007

Bavaria, Augsburg, Germany

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Cited By

Shen LHong RHao Y(2020)Advance on large scale near-duplicate video retrievalFrontiers of Computer Science10.1007/s11704-019-8229-714:5Online publication date: 3-Jan-2020
https://doi.org/10.1007/s11704-019-8229-7
Héritier MGagnon LFoucher S(2018)Places clustering of full-length film key-framesusing latent aspect modeling over SIFT matchesIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2009.201730419:6(832-841)Online publication date: 31-Dec-2018
https://dl.acm.org/doi/10.1109/TCSVT.2009.2017304
Li YChen X(2017)Robust and compact video descriptor learned by deep neural network2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2017.7952539(2162-2166)Online publication date: Mar-2017
https://doi.org/10.1109/ICASSP.2017.7952539
Liu JHuang ZCai HShen HNgo CWang W(2013)Near-duplicate video retrievalACM Computing Surveys (CSUR)10.1145/2501654.250165845:4(1-23)Online publication date: 30-Aug-2013
https://dl.acm.org/doi/10.1145/2501654.2501658
Hong LLu HXue X(2013)A Segmentation and Graph-Based Video Sequence Matching Method for Video Copy DetectionIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2012.9225:8(1706-1718)Online publication date: 1-Aug-2013
https://dl.acm.org/doi/10.1109/TKDE.2012.92
Liu HLu HWen ZXue X(2012)Gradient Ordinal Signature and Fixed-Point Embedding for Efficient Near-Duplicate Video DetectionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2011.216829422:4(555-566)Online publication date: 1-Apr-2012
https://dl.acm.org/doi/10.1109/TCSVT.2011.2168294
Liu JHuang ZShen HCui B(2011)Correlation-based retrieval for heavily changed near-duplicate videosACM Transactions on Information Systems10.1145/2037661.203766629:4(1-25)Online publication date: 8-Dec-2011
https://dl.acm.org/doi/10.1145/2037661.2037666
Wei SZhao YZhu CXu CZhu Z(2011)Frame Fusion for Video Copy DetectionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2011.210555421:1(15-28)Online publication date: 1-Jan-2011
https://dl.acm.org/doi/10.1109/TCSVT.2011.2105554
Bailer WLi SGao XSebe N(2010)Evaluating detection of near duplicate video segmentsProceedings of the ACM International Conference on Image and Video Retrieval10.1145/1816041.1816072(197-204)Online publication date: 5-Jul-2010
https://dl.acm.org/doi/10.1145/1816041.1816072
Liu HLu HXue X(2010)SVD-SIFT for web near-duplicate image detection2010 IEEE International Conference on Image Processing10.1109/ICIP.2010.5650235(1445-1448)Online publication date: Oct-2010
https://doi.org/10.1109/ICIP.2010.5650235
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