Denis Teyssou
Evlampios Apostolidis
Symeon Papadopoulos
ABSTRACT
This paper presents a novel open-source browser plug-in that aims at supporting journalists and news professionals in their efforts to verify user-generated video. The plug-in, which is the result of an iterative design thinking methodology, brings together a number of sophisticated multimedia analysis components and third party services, with the goal of speeding up established verification workflows and making it easy for journalists to access the results of different services that were previously used as standalone tools. The tool has been downloaded several hundreds of times and is currently used by journalists worldwide, after being tested by Agence France-Presse (AFP) and Deutsche Welle (DW) journalists and media researchers for a few months. The tool has already helped debunk a number of fake videos.
- E. Apostolidis and V. Mezaris. 2014. Fast Shot Segmentation Combining Global and Local Visual Descriptors. In Proceedings of the 2014 IEEE International Conference on Acoustics, Speech and Signal Processing. 6583--6587. Software available at http://mklab.iti.gr/project/video-shot-segm.Google Scholar
- L. Bai, Y. Hu, S. Lao, A. F. Smeaton, and N. E. O'Connor. 2010. Automatic Summarization of Rushes Video Using Bipartite Graphs. Multimedia Tools and Applications 49, 1 (Aug. 2010), 63--80. Google ScholarDigital Library
- L. Baraldi, C. Grana, and R. Cucchiara. 2015. Shot and Scene Detection via Hierarchical Clustering for Re-using Broadcast Video. Springer International Publishing, Cham, 801--811.Google Scholar
- G. K. Birajdar and V. H. Mankar. 2013. Digital Image Forgery Detection Using Passive Techniques: A Survey. Digital Investigation 10, 3 (2013), 226--245. Google ScholarDigital Library
- C. Boididou, S. Papadopoulos, L. Apostolidis, and Y. Kompatsiaris. 2017. Learning to Detect Misleading Content on Twitter. In Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval. ACM, 278--286. Google ScholarDigital Library
- C. Castillo, M. Mendoza, and B. Poblete. 2013. Predicting Information Credibility in Time-sensitive Social Media. Internet Research 23, 5 (2013), 560--588.Google ScholarCross Ref
- J. Chao, X. Jiang, and T. Sun. 2012. A Novel Video Inter-frame Forgery Model Detection Scheme Based on Optical Flow Consistency. In IWDW (Lecture Notes in Computer Science), Yun Q. Shi, Hyoung-Joong Kim, and Fernando Pérez-González (Eds.), Vol. 7809. Springer, 267--281. Google ScholarDigital Library
- W.-T. Chu, P.-C. Chuang, and J.-Y. Yu. 2010. Video Copy Detection Based on Bag of Trajectory and Two-Level Approximate Sequence Matching. In Proceedings of the IPPR Conference on Computer Vision, Graphics, and Image Processing Conference.Google Scholar
- S. H. Cooray, H. Bredin, L.-Q. Xu, and N. E. O'Connor. 2009. An Interactive and Multi-level Framework for Summarising User Generated Videos. In Proceedings of the 17th ACM International Conference on Multimedia (MM '09). ACM, New York, NY, USA, 685--688. Google ScholarDigital Library
- E. Dumont, B. Merialdo, S. Essid, W. Bailer, H. Rehatschek, D. Byrne, H. Bredin, N. E. O'Connor, G. J. F. Jones, A. F. Smeaton, M. Haller, A. Krutz, T. Sikora, and T. Piatrik. 2008. Rushes Video Summarization Using a Collaborative Approach. In TRECVID 2008, ACM International Conference on Multimedia Information Retrieval 2008, October 27 - November 01, 2008, Vancouver, BC, Canada. Vancouver, CANADA. Google ScholarDigital Library
- A. C. S. e Santos and H. Pedrini. 2016. Adaptive Video Shot Detection Improved by Fusion of Dissimilarity Measures. In Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 002948--002953.Google Scholar
- H. Farid. 2009. Exposing Digital Forgeries from JPEG Ghosts. IEEE Transactions on Information Forensics and Security 4, 1 (2009), 154--160. Google ScholarDigital Library
- H. Farid. 2016. Photo Forensics. MIT Press. Google ScholarDigital Library
- A. Gironi, M. Fontani, T. Bianchi, A. Piva, and M. Barni. 2014. A Video Forensic Technique for Detecting Frame Deletion and Insertion. In ICASSP. IEEE, 6226-- 6230.Google Scholar
- I. González-Díaz, T. Martínez-Cortés, A. Gallardo-Antolín, and F. Díaz-de María. 2015. Temporal Segmentation and Keyframe Selection Methods for Usergenerated Video Search-based Annotation. Expert Systems with Applications 42, 1 (Jan. 2015), 488--502. Google ScholarDigital Library
- A. Gupta, H. Lamba, P. Kumaraguru, and A. Joshi. 2013. Faking Sandy: Characterizing and Identifying Fake Images on Twitter During Hurricane Sandy. In Proceedings of the 22nd international conference on World Wide Web. ACM, 729--736. Google ScholarDigital Library
- S. Karaman, J. Benois-Pineau, V. Dovgalecs, R. Mégret, J. Pinquier, R. André- Obrecht, Y. Gaëstel, and J.-F. Dartigues. 2014. Hierarchical Hidden Markov Model in Detecting Activities of Daily Living in Wearable Videos for Studies of Dementia. Multimedia Tools and Applications 69, 3 (2014), 743--771. Google ScholarDigital Library
- E. Kasutani and A. Yamada. 2001. The MPEG-7 Color Layout Descriptor: A Compact Image Feature Description for High-speed Image/Video Segment Retrieval. In Proceedings of the 2001 International Conference on Image Processing (Cat. No.01CH37205), Vol. 1. 674--677.Google Scholar
- P. Kelm, S. Schmiedeke, and T. Sikora. 2009. Feature-based Video Key Frame Extraction for Low Quality Video Sequences. In 10th Workshop on Image Analysis for Multimedia Interactive Services. 25--28.Google Scholar
- N. Krawetz. 2007. A Picture's Worth... Digital Image Analysis and Forensics. Online article on: http://www.hackerfactor.com/papers/bh-usa-07-krawetz-wp.pdf. (2007). Accessed: 2016-02-26.Google Scholar
- W. Li, Y. Yuan, and N. Yu. 2009. Passive Detection of Doctored JPEG Image via Block Artifact Grid Extraction. Signal Processing 89, 9 (2009), 1821--1829. Google ScholarDigital Library
- Z. Lin, J. He, X. Tang, and C.-K. Tang. 2009. Fast, Automatic and Fine-grained Tampered JPEG Image Detection via DCT Coefficient Analysis. Pattern Recognition 42, 11 (2009), 2492--2501. Google ScholarDigital Library
- Y. Liu, Y. Liu, T. Ren, and K. C. C. Chan. 2008. Rushes Video Summarization Using Audio-visual Information and Sequence Alignment. In Proceedings of the 2nd ACM TRECVid Video Summarization Workshop (TVS '08). ACM, New York, NY, USA, 114--118. Google ScholarDigital Library
- Z. Lu and K. Grauman. 2013. Story-Driven Summarization for Egocentric Video. In Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR '13). IEEE Computer Society, Washington, DC, USA, 2714--2721. Google ScholarDigital Library
- J. Luo, C. Papin, and K. Costello. 2009. Towards Extracting Semantically Meaningful Key Frames from Personal Video Clips: From Humans to Computers. IEEE Transactions on Circuits and Systems for Video Technology 19, 2 (Feb. 2009), 289--301. Google ScholarDigital Library
- B. Mahdian and S. Saic. 2009. Using Noise Inconsistencies for Blind Image Forensics. Image and Vision Computing 27, 10 (2009), 1497--1503. Google ScholarDigital Library
- T. Mei, L.-X. Tang, J. Tang, and X.-S. Hua. 2013. Near-lossless Semantic Video Summarization and Its Applications to Video Analysis. ACM Transactions on Multimedia Computing, Communications and Applications 9, 3, Article 16 (July 2013), 23 pages. Google ScholarDigital Library
- M. Nekovee, Y. Moreno, G. Bianconi, and M. Marsili. 2007. Theory of Rumour Spreading in Complex Social Networks. Physica A: Statistical Mechanics and its Applications 374, 1 (2007), 457--470.Google Scholar
- C.-M. Pan, Y.-Y. Chuang, and W. H. Hsu. 2007. NTU TRECVID-2007 Fast Rushes Summarization System. In Proceedings of the International Workshop on TRECVID Video Summarization (TVS '07). ACM, New York, NY, USA, 74--78. Google ScholarDigital Library
- R. C. Pandey, Sanjay K. S., and K. K. Shukla. 2016. Passive Forensics in Image and Video Using Noise Features: A Review. Digital Investigation 19 (2016), 1--28. Google ScholarDigital Library
- O. Papadopoulou, M. Zampoglou, S. Papadopoulos, and Y. Kompatsiaris. 2017. Web Video Verification Using Contextual Cues. In Proceedings of the 2nd International Workshop on Multimedia Forensics and Security (MFSec '17). ACM, New York, NY, USA, 6--10. Google ScholarDigital Library
- V. Qazvinian, E. Rosengren, D. R. Radev, and Q. Mei. 2011. Rumor Has It: Identifying Misinformation in Microblogs. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP '11). Association for Computational Linguistics, Stroudsburg, PA, USA, 1589--1599. Google ScholarDigital Library
- C. Silverman. 2014. Verification Handbook: A Definitive Guide to Verifying Digital Content for Emergency Coverage. European Journalism Centre.Google Scholar
- K. Sitara and B. M. Mehtre. 2016. Digital Video Tampering Detection: An Overview of Passive Techniques. Digital Investigation 18 (2016), 8--22. Google ScholarDigital Library
- M. C. Stamm, M. Wu, and K. J. R. Liu. 2013. Information Forensics: An Overview of the First Decade. IEEE Access 1 (2013), 167--200.Google ScholarCross Ref
- S. Tippaya, S. Sitjongsataporn, T. Tan, K. Chamnongthai, and M. Khan. 2015. Video Shot Boundary Detection Based on Candidate Segment Selection and Transition Pattern Analysis. In Proceedings of the 2015 IEEE International Conference on Digital Signal Processing (DSP). 1025--1029.Google Scholar
- M. Verma and B. Raman. 2017. A Hierarchical Shot Boundary Detection Algorithm Using Global and Local Features. Springer Singapore, Singapore, 389--397.Google Scholar
- A. Vlachos and S. Riedel. 2014. Fact Checking: Task Definition and Dataset Construction. In Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science. 18--22.Google Scholar
- J. Xu, L. Mukherjee, Y. Li, J. Warner, J. M. Rehg, and V. Singh. 2015. Gaze-enabled Egocentric Video Summarization via Constrained Submodular Maximization. In Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR '15). IEEE Computer Society, 2235--2244.Google Scholar
- M. Zampoglou, S. Papadopoulos, and Y. Kompatsiaris. 2015. Detecting Image Splicing in the Wild (Web). In Proceedings of the 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW). IEEE, 1--6.Google Scholar
- M. Zampoglou, S. Papadopoulos, and Y. Kompatsiaris. 2017. Large-scale Evaluation of Splicing Localization Algorithms for Web Images. Multimedia Tools and Applications 76, 4 (Feb. 2017), 4801--4834. Google ScholarDigital Library
- M. Zampoglou, S. Papadopoulos, Y. Kompatsiaris, R. Bouwmeester, and J. Spangenberg. 2016. Web and Social Media Image Forensics for News Professionals.. In Social Media In the NewsRoom, #SMNews16@CWSM, Tenth International AAAI Conference on Web and Social Media workshops.Google Scholar
Index Terms
- The InVID Plug-in: Web Video Verification on the Browser
Recommendations
Web Video Verification using Contextual Cues
MFSec '17: Proceedings of the 2nd International Workshop on Multimedia Forensics and SecurityAs news agencies and the public increasingly rely on User-Generated Content, content verification is vital for news producers and consumers alike. We present a novel approach for verifying Web videos by analyzing their online context. It is based on ...
A Study of Tweet Veracity to Separate Rumours from Counter-Rumours
#SMSociety17: Proceedings of the 8th International Conference on Social Media & SocietyRumours are known to propagate easily through computer-mediated communication channels such as Twitter. Their outbreak is often followed by the spread of 'counter-rumours', which are messages that debunk rumours. The probability of a tweet to be a ...
Advertising to Early Trend Propagators: Evidence from Twitter
In the digital economy, influencing and controlling the spread of information is a key concern for firms. One way firms try to achieve this is to target firm communications to consumers who embrace and propagate the spread of new information on emerging ...
Comments