Abstract
Pictures spreading on the Internet are essential for the authenticity of events. Each day, huge amounts of data are published on social media, and many of them are bound with a picture in order to increase their readability and reliability. On social media, the bound pictures often have little relevance to their context. The thing changes when it comes to events in our daily lives. The events on social media are often bound with the spot shooting. People are more willing to believe the events described by these pictures. Nevertheless, it is nightmare to plow through millions of pictures which contain enormous noises and redundancies on social media. Moreover, in order to attract readers, the dishonest often mislead the public, by spreading sensational sham news with specious pictures. This behave severely destroys the honesty in our society. In this paper, we visualize an event from its bound pictures, based on the consistency between picture and event. First, we extract high reliable pictures for the event, by analyzing the consistency on temporal and textual dimensions. Second, the consistency of pictures is optimized in a related picture graph, in order to push up representative pictures of an event. The experiments on a real dataset verify the effectiveness of our method in most cases, comparing to several up-to-date methods.
Similar content being viewed by others
References
Alqadah F, Bhatnagar R (2011) A game theoretic framework for heterogenous information network clustering. In: Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 795–804
Bertini M, Del Bimbo A, Torniai C (2005) Enhanced ontologies for video annotation and retrieval. In: Proceedings of the 7th ACM SIGMM international workshop on multimedia information retrieval. ACM, pp 89–96
Bronstein MM, Bronstein AM, Michel F, Paragios N (2010) Data fusion through cross-modality metric learning using similarity-sensitive hashing. In: IEEE Conference on computer vision and pattern recognition. IEEE, pp 3594–3601
Cao Y, O Halloran K (2014) Learning human photo shooting patterns from large-scale community photo collections. Multimed Tools Appl 74(24):11,499–11,516
Cheng X, Dale C, Liu J (2008) Statistics and social network of youtube videos. In: 2008 16th International workshop on quality of service. IEEE, pp 229–238
Cui B, Tung A K, Zhang C, Zhao Z (2010) Multiple feature fusion for social media applications. In: Proceedings of the 2010 ACM SIGMOD international conference on management of data. ACM, 435–446
Dao M S, Dang-Nguyen D T, De Natale F G (2014) Robust event discovery from photo collections using signature image bases (sibs). Multimed Tools Appl 70 (1):25–53
Dekel T, Moses Y, Avidan S (2013) Space-time tradeoffs in photo sequencing. In: Proceedings of the IEEE international conference on computer vision. IEEE, pp 977–984
Gozali J P, Kan M Y, Sundaram H (2012) Hidden markov model for event photo stream segmentation. In: Proceedings of the 2012 IEEE International conference on multimedia and expo workshops. IEEE, pp 25–30
Hsieh L C, Wu G L, Hsu Y M, Hsu W (2014) Online image search result grouping with mapreduce-based image clustering and graph construction for large-scale photos. J Vis Commun Image Represent 25(2):384–395
Hua XS, Yang L, Wang J, Wang J, Ye M, Wang K, Rui Y, Li J (2013) Clickage: towards bridging semantic and intent gaps via mining click logs of search engines. In: Proceedings of the 21st ACM international conference on multimedia. ACM, pp 243–252
Jin F (2013) Research on residents extraction of rs images based on texture feature. PhD thesis, The PLA Information Engineering University
Kaneko T, Yanai K (2015) Event photo mining from twitter using keyword bursts and image clustering. Neurocomputing 172:143–158
Kasutani E, Yamada A (2001) The mpeg-7 color layout descriptor: a compact image feature description for high-speed image/video segment retrieval. In: Proceedings of the 2001 IEEE International conference on image processing, vol 1. IEEE, pp 674–677
Kumar S, Udupa R (2011) Learning hash functions for cross-view similarity search. In: Proceedings of the 22nd International joint conference on artificial intelligence, pp 1360–1365
Luo J, Yu J, Joshi D, Hao W (2008) Event recognition: viewing the world with a third eye. In: Proceedings of the 16th ACM international conference on multimedia. ACM, pp 1071–1080
McParlane PJ, McMinn AJ, Jose JM (2014) Picture the scene...; visually summarising social media events. In: Proceedings of the 23rd ACM international conference on information and knowledge management. ACM, pp 1459–1468
Plantié M, Crampes M (2010) From photo networks to social networks, creation and use of a social network derived with photos. In: Proceedings of the 2010 ACM international conference on multimedia. ACM, pp 1047–1050
Rafailidis D, Manolopoulou S, Daras P (2013) A unified framework for multimodal retrieval. Pattern Recog 46(12):3358–3370
Rasiwasia N, Costa Pereira J, Coviello E, Doyle G, Lanckriet GR, Levy R, Vasconcelos N (2010) A new approach to cross-modal multimedia retrieval. In: Proceedings of the 18th ACM international conference on multimedia. ACM, pp 251–260
Rosani A, Boato G, De Natale F G (2015) Eventmask: a game-based framework for event-saliency identification in images. IEEE Trans Multimed 17(8):1359–1371
Ruocco M, Ramampiaro H (2014) A scalable algorithm for extraction and clustering of event-related pictures. Multimed Tools Appl 70(1):55–88
Sivic J, Zisserman A (2003) Video google: a text retrieval approach to object matching in videos. In: Proceedings of the 9th IEEE international conference on computer vision. IEEE, pp 1470–1477
Sun Y, Aggarwal C C, Han J (2012a) Relation strength-aware clustering of heterogeneous information networks with incomplete attributes. Proc VLDB Endowment 5(5):394–405
Sun Y, Han J, Aggarwal CC, Chawla NV (2012b) When will it happen?: relationship prediction in heterogeneous information networks. In: Proceedings of the 5th ACM international conference on web search and data mining. ACM, pp 663–672
Wang C, Danilevsky M, Liu J, Desai N, Ji H, Han J (2013) Constructing topical hierarchies in heterogeneous information networks. In: Proceedings of the 13th IEEE International conference on data mining. IEEE, pp 767–776
Wang W, Ooi B C, Yang X, Zhang D, Zhuang Y (2014) Effective multi-modal retrieval based on stacked auto-encoders. Proc VLDB Endowment 7(8):649–660
Wang Y, Sundaram H, Xie L (2012) Social event detection with interaction graph modeling. In: Proceedings of the 20th ACM International conference on multimedia. ACM, pp 865–868
Won C S, Park D K, Park S J (2002) Efficient use of mpeg-7 edge histogram descriptor. ETRI J 24(1):23–30
Wu F, Yang Y, Zhuang Y, Pan Y (2005) Understanding multimedia document semantics for cross-media retrieval. In: Advances in multimedia information processing-PCM 2005. Springer, pp 993–1004
Wu F, Yu Z, Yang Y, Tang S, Zhang Y, Zhuang Y (2014) Sparse multi-modal hashing. IEEE Trans Multimed 16(2):427–439
Xiong Y, Wang D, Zhang Y, Feng S, Wang G (2014) Multimodal data fusion in text-image heterogeneous graph for social media recommendation. In: Web-Age information management. Springer, pp 96–99
Yang F, Huang Q, Jin L, Liew A W C (2016) Segmentation and recognition of multi-model photo event. Neurocomputing 172:159–167
Yang Y, Xu D, Nie F, Luo J, Zhuang Y (2009) Ranking with local regression and global alignment for cross media retrieval. In: Proceedings of the 17th ACM International conference on multimedia. ACM, pp 175–184
Yang Y, Wu F, Xu D, Zhuang Y, Chia L T (2010) Cross-media retrieval using query dependent search methods. Pattern Recogn 43(8):2927–2936
Zhang H, Weng J (2006) Measuring multi-modality similarities via subspace learning for cross-media retrieval. In: Advances in multimedia information processing-PCM 2006. Springer, pp 979–988
Zhao X, Zhu F, Qian W, Zhou A (2013) Impact of multimedia in sina weibo: popularity and life span. In: Semantic web and web science. Springer, pp 55–65
Acknowledgments
The project is supported by National Natural Science Foundation of China (61402091, 61370074), the Fundamental Research Funds for the Central Universities of China under Grant N140404012.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Xiong, Y., Zhang, Y., Wang, D. et al. Picture or it didn’t happen: catch the truth for events. Multimed Tools Appl 76, 15681–15706 (2017). https://doi.org/10.1007/s11042-016-3864-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-016-3864-6