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ENF Signal Induced by Power Grid: A New Modality for Video Synchronization

Authors:

Adi Hajj-Ahmad,

Min WuAuthors Info & Claims

ImmersiveMe '14: Proceedings of the 2nd ACM International Workshop on Immersive Media Experiences

Pages 13 - 18

https://doi.org/10.1145/2660579.2660588

Published: 07 November 2014 Publication History

Abstract

Multiple videos capturing the same scene from possibly different viewing angles may be synthesized for novel immersive experience. Synchronization is an important task for such applications involving multiple pieces of audio-visual data. In this work, we exploit the electric network frequency (ENF) signal inherently embedded in the soundtrack and/or image sequence of video to temporally align video recordings. ENF is the supply frequency of power distribution networks in a power grid. Its value fluctuates slightly from its nominal value of 50 Hz or 60 Hz, and the fluctuation trends stay consistent within the same grid. Audio and video recordings that are created in areas of electric activities may capture the ENF signal due to electromagnetic interferences and other physical phenomena. We propose to synchronize video recordings by aligning the embedded ENF signals. Without major constraints on viewing angle and camera calibration as many existing methods impose, the proposed approach emerges as a new synchronization modality.

References

[1]

E. Shechtman, Y. Caspi, and M. Irani, "Space-time super-resolution," IEEE Trans. Pattern Anal. Mach. Intell., Apr. 2005.

Digital Library

[2]

M. El-Saban, A. Kaheel, and M. Refaat, "Stitching videos streamed by mobile phones in real-time," in ACM Multimedia.

Digital Library

[3]

G. P. Stein, "Tracking from multiple view points: self-calibration of space and time," in Int'l Conf. Comput. Vision & Pattern Recognition, 1999.

[4]

Y. Caspi and M. Irani, "A step towards sequence -to-sequence alignment," in Int'l Conf. Comput. Vision & Pattern Recognition, 2000.

[5]

T. Tuytelaars and L. V. Gool, "Synchronizing video sequences," in Int'l Conf. Comput. Vision & Pattern Recognition, 2004.

[6]

Y. Caspi, D. Simakov, and M. Irani, "Feature-based sequence-to-sequence matching," Int'l J. Comput. Vision, vol. 68(1), Jun. 2006.

Digital Library

[7]

P. Shrestha, H. Weda, M. Barbieri, and D. Sekulovski, "Synchronization of multiple video recordings based on still camera flashes," in ACM Multimedia, 2006.

Digital Library

[8]

F. Padua, R. Carceroni, G. Santos, and K. Kutulakos, "Linear sequence-to-sequence alignment," IEEE Trans. Pattern Anal. Mach. Intell., vol. 32(2), Feb. 2010.

Digital Library

[9]

C. Grigoras, "Applications of ENF analysis in forensic authentication of digital and video recordings," J. Audio Eng. Soc., 2009.

[10]

R. Garg, A. Varna, and M. Wu, "Seeing ENF: Natural time stamp for digital video via optical sensing and signal processing," in ACM Multimedia, 2011.

Digital Library

[11]

R. W. Sanders, "Digital authenticity using the electric network frequency," in 33rd AES Int'l Conf. Audio Forensics, Theory & Practice, Jun. 2008.

[12]

D. Rodriguez, J. Apolinario, and L. Biscainho, "Audio authenticity: Detecting ENF discontinuity with high precision phase analysis," IEEE Trans. Inf. Forensics & Security, vol. 5(3), pp. 534--543, Sep. 2010.

Digital Library

[13]

C.-K. Liang, L.-W. Chang, and H. H. Chen, "Analysis and compensation of rolling shutter effect," IEEE Trans. Image Process., vol. 17(8), pp. 1323--1330, 2008.

Digital Library

[14]

O. Ait-Aider, A. Bartoli, and N. Andreff, "Kinematics from lines in a single rolling shutter image," in Int'l Conf. Comput. Vision & Pattern Recognition (CVPR), 2007.

[15]

J. Gu, Y. Hitomi, T. Mitsunaga, and S. Nayar, "Coded rolling shutter photography: Flexible space-time sampling," in IEEE Int'l Conf. Comput. Photography (ICCP), 2010.

[16]

R. Garg, A. L. Varna, A. Hajj-Ahmad, and M. Wu, "Seeing ENF: Power signature based timestamp for digital multimedia via optical sensing and signal processing," IEEE Trans. Inf. Forensics & Security, vol. 8(9), 2013.

Digital Library

[17]

C. Liu, "Beyond pixels: Exploring new representations and applications for motion analysis," Doctoral Thesis, Massachusetts Institute of Technology, May 2009.

Digital Library

Cited By

Berk Yalinkiliç AVatansever S(2024)An Enhanced STFT Segmentation Framework for ENF-Based Media ForensicsIEEE Access10.1109/ACCESS.2024.344909912(117850-117862)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3449099
Ngharamike EAng LSeng KWang M(2023)Exploiting the Rolling Shutter Read-Out Time for ENF-Based Camera IdentificationApplied Sciences10.3390/app1308503913:8(5039)Online publication date: 17-Apr-2023
https://doi.org/10.3390/app13085039
Choi JWong CSu HWu M(2023)Analysis of ENF Signal Extraction From Videos Acquired by Rolling ShuttersIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.328713218(4229-4242)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3287132
Show More Cited By

Index Terms

ENF Signal Induced by Power Grid: A New Modality for Video Synchronization
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Scene understanding
2. Information systems
  1. Information systems applications
    1. Multimedia information systems

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Information & Contributors

Information

Published In

cover image ACM Conferences

ImmersiveMe '14: Proceedings of the 2nd ACM International Workshop on Immersive Media Experiences

November 2014

58 pages

ISBN:9781450331227

DOI:10.1145/2660579

Program Chairs:
Teresa Chambel
Lasige, Fac of Sciences, Univ of Lisbon, Portugal
,
Paula Viana
Polytechnic of Porto and INESC TEC, Portugal
,
V. Michael Bove
MIT Media Lab, USA
,
Sharon Strover
University of Texas at Austin, USA
,
Graham Thomas
BBC, UK

Copyright © 2014 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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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 November 2014

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Funding Sources

National Science Foundation

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MM '14

Sponsor:

SIGMM

MM '14: 2014 ACM Multimedia Conference

November 7, 2014

Florida, Orlando, USA

Acceptance Rates

ImmersiveMe '14 Paper Acceptance Rate 5 of 12 submissions, 42%;

Overall Acceptance Rate 11 of 31 submissions, 35%

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Cited By

Berk Yalinkiliç AVatansever S(2024)An Enhanced STFT Segmentation Framework for ENF-Based Media ForensicsIEEE Access10.1109/ACCESS.2024.344909912(117850-117862)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3449099
Ngharamike EAng LSeng KWang M(2023)Exploiting the Rolling Shutter Read-Out Time for ENF-Based Camera IdentificationApplied Sciences10.3390/app1308503913:8(5039)Online publication date: 17-Apr-2023
https://doi.org/10.3390/app13085039
Choi JWong CSu HWu M(2023)Analysis of ENF Signal Extraction From Videos Acquired by Rolling ShuttersIEEE Transactions on Information Forensics and Security10.1109/TIFS.2023.328713218(4229-4242)Online publication date: 2023
https://doi.org/10.1109/TIFS.2023.3287132
Vatansever SDirik AMemon N(2023)The Effect of Inverse Square Law of Light on ENF in Videos Exposed by Rolling ShutterIEEE Transactions on Information Forensics and Security10.1109/TIFS.2022.322002918(248-260)Online publication date: 2023
https://doi.org/10.1109/TIFS.2022.3220029
Ngharamike EAng LSeng KWang M(2023)ENF Based Digital Multimedia Forensics: Survey, Application, Challenges and Future WorkIEEE Access10.1109/ACCESS.2023.331218111(101241-101272)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3312181
Vatansever S(2023)A Thorough Investigation Into the ENF Reconstruction in Videos Exposed by Rolling ShutterIEEE Access10.1109/ACCESS.2023.331203011(96330-96342)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3312030
Frijters GGeradts Z(2022)Use of electric network frequency presence in video material for time estimationJournal of Forensic Sciences10.1111/1556-4029.1500367:3(1021-1032)Online publication date: 4-Feb-2022
https://doi.org/10.1111/1556-4029.15003
Choi JWong CHajj-Ahmad AWu MRen Y(2022)Invisible Geolocation Signature Extraction From a Single ImageIEEE Transactions on Information Forensics and Security10.1109/TIFS.2022.318577517(2598-2613)Online publication date: 2022
https://doi.org/10.1109/TIFS.2022.3185775
Poredi NNagothu DChen YLi XAved AArdiles-Cruz EBlasch E(2022)Robustness of Electrical Network Frequency Signals as a Fingerprint for Digital Media Authentication2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP55362.2022.9949315(1-6)Online publication date: 26-Sep-2022
https://doi.org/10.1109/MMSP55362.2022.9949315
Vatansever SDirik AMemon N(2022)ENF Based Robust Media Time-StampingIEEE Signal Processing Letters10.1109/LSP.2022.320556329(1963-1967)Online publication date: 2022
https://doi.org/10.1109/LSP.2022.3205563
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