Predicting celebrity attendees at public events using stock photo metadata


The large collections of news images available from stock photo agencies provide interesting insights into how different celebrities are related to each other, in terms of the events they attend together and also in terms of how often they are photographed together. In this paper, we leverage such collections to predict which celebrities will attend future events. The main motivation for this is in the event-based indexing of online collections of multimedia content, an area that has attracted much attention in recent years. Based on the metadata associated with a corpus of stock photos, we propose a language model for predicting celebrities attending future events. A temporal hierarchical version of the language model exploits fresh data while still making use of all historical data. We extract a social network from co-appearance of public figures in the events depicted in the photographs, and combine this latent social information with the language model to further improve prediction accuracy. The experimental results show that combining textual, network and temporal information gives the best prediction performance. Our analysis also shows that the prediction models, when trained by the most recent data, are most accurate for political and sports events.

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  1. 1.

    The largest agencies are Getty Images, Corbis, and Sipa Press.

  2. 2.

  3. 3.


  1. 1.

    Ahmed A, Batagelj V, Fu X, Hong S-H, Merrick D, Mrvar A (2007) Visualisation and analysis of the internet movie database. In APVIS, pp 17–24

  2. 2.

    Aiello LM, Barrat A, Cattuto C, Ruffo G, Schifanella R (2010) Link creation and profile alignment in the anobii social network. In. Proceedings of the 2010 IEEE Second International Conference on Social Computing, SOCIALCOM ’10, pp. 249–256, Washington. IEEE Computer Society

  3. 3.

    Aiello LM, Barrat A, Schifanella R, Cattuto C, Markines B, Menczer F (2012) Friendship prediction and homophily in social media. ACM Trans Web 6(2):9:1–9:33

    Article  Google Scholar 

  4. 4.

    Anguelov D, Lee K-C, Gokturk SB, Sumengen B (2007) Contextual Identity Recognition in Personal Photo Albums. In IEEE CVPR, pp 1–7

  5. 5.

    Aragon P, Kaltenbrunner A, Laniado D, Volkovich Y (2012) Biographical social networks on wikipedia - a cross-cultural study of links that made history. Arxiv preprint arXiv, pp 4

  6. 6.

    Becker H, Naaman M, Gravano L (2010) Learning similarity metrics for event identification in social media. In Proceedings of the third ACM international conference on Web search and data mining, WSDM ’10, pp 291–300. ACM, New York

    Google Scholar 

  7. 7.

    Blei DM, Ng AY, Jordan MI (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022

    MATH  Google Scholar 

  8. 8.

    Brenner M, Ebroul I (2013) Mediaeval 2013: Social event detection, retrieval and classification in collaborative photo collections. In: Larson MA, Anguera X, Reuter T, Jones GJF, Ionescu B, Schedl M, Piatrik T, Hauff C, Soleymani M (eds) MediaEval, volume 1043 of CEUR Workshop Proceedings.

  9. 9.

    Chen L, Roy A (2009) Event detection from flickr data through wavelet-based spatial analysis. In CIKM, pp 523–532. ACM

  10. 10.

    Cooper M, Foote J, Girgensohn A, Wilcox L (2005) Temporal event clustering for digital photo collections. ACM Trans Multimedia Comput Commun Appl 1(3):269–288

    Article  Google Scholar 

  11. 11.

    Davis M., Smith M, Canny J, Good N, King S, Janakiraman R (2005) Towards context-aware face recognition.. In: Proceedings of the 13th annual ACM international conference on Multimedia, MULTIMEDIA ’05. ACM, New York, pp 483–486

  12. 12.

    Devezas J, Coelho F, Nunes S, Ribeiro C (2012) Studying a personality coreference network in a news stories photo collection. In: Proceedings of the 34th European conference on Advances in Information Retrieval, ECIR’12, pp 485–488. Springer, Berlin

    Google Scholar 

  13. 13.

    Griffiths TL, Steyvers M (2004) Finding scientific topics. Proc Natl Acad Sci 101(1):5228–5235

    Article  Google Scholar 

  14. 14.

    Jelinek F, Mercer RL (1980) Interpolated estimation of markov source parameters from sparse data. In: Proceedings of the Workshop on Pattern Recognition in Practice, pp 381–397, Amsterdam, The Netherlands: North-Holland

  15. 15.

    Kim H-N, Jung J-G, El Saddik A (2010) Associative face co-occurrence networks for recommending friends in social networks.. In: Proceedings of second ACM SIGMM workshop on Social media, WSM ’10. ACM, pp 27–32

  16. 16.

    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, MM ’08. ACM, New York, pp 1071–1080

  17. 17.

    Mantrach A, Renders J-M (2012) A general framework for people retrieval in social media with multiple roles.. In: Proceedings of the 34th European conference on Advances in Information Retrieval, ECIR’12. Springer-Verlag, Berlin, Heidelberg, pp 512–516

  18. 18.

    Mavridis N, Kazmi W, Toulis P (2010) Friends with faces: How social networks can enhance face recognition and vice versa. In: Abraham A, Hassanien AE, Snasel V (eds) Computational Social Network Analysis, Computer Communications and Networks, pp 453–482. Springer, London

  19. 19.

    Naaman M, Yeh RB, Garcia-Molina H, Paepcke A (2005) Leveraging context to resolve identity in photo albums. In JCDL, pp 178–187. ACM

  20. 20.

    O’Hare N, Aiello LM, Jaimes A (2012) Predicting participants in public events using stock photos.. In: Proceedings of the 20th ACM international conference on Multimedia, MM ’12. ACM, New York, pp 1093–1096

  21. 21.

    O’Hare N, Murdock V (2013) Modeling locations with social media. Inf Retr 16:30–62

    Article  Google Scholar 

  22. 22.

    O’Hare N, Smeaton AF (2009) Context-aware person identification in personal photo collections. IEEE Transactions on Multimedia, Special Issue on Integration of Context and Content for Multimedia Management 11(2):220–228

    Google Scholar 

  23. 23.

    Petkos G, Papadopoulos S, Mezaris V, Troncy R, Cimiano P, Reuter T, Kompatsiaris Y (2014) Social event detection at mediaeval: a three-year retrospect of tasks and results. In: ICMR 2014 Workshop on Social Events in Web Multimedia (SEWM). ACM, Glasgow

    Google Scholar 

  24. 24.

    Ponte JM, Bruce Croft W. (1998) A language modeling approach to information retrieval.. In: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’98. ACM, New York, pp 275–281

  25. 25.

    Rattenbury T, Good N, Naaman M (2007) Towards automatic extraction of event and place semantics from flickr tags.. In: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’07. ACM, New York, pp 103–110

  26. 26.

    Samangooei S, Hare JS, Dupplaw D, Niranjan M, Gibbins N, Lewis PH, Davies J, Jain N, Preston J (2013) Social event detection via sparse multi-modal feature selection and incremental density based clustering. In MediaEval’13, pp –1–1

  27. 27.

    Serdyukov P, Murdock V, van Zwol R (2009) Placing Flickr Photos on a Map.. In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, pp 484–491

  28. 28.

    Singla P, Kautz H, Luo J, Gallagher A (2008) Discovery of social relationships in consumer photo collections using markov logic.. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW ’08, pp 1–7

  29. 29.

    Sivic J, Zitnick CL, Szeliski R (2006) Finding People in Repeated Shots of the Same Scene.. In: Proceedings of the British Machine Vision Conference. Edinburgh, pp 909–918

  30. 30.

    Smucker MD, Allan J (2005) An investigation of dirichlet prior smoothing’s performance advantage. Technical report, The Center for Intelligent Information Retrieval, The University of Massachusetts

  31. 31.

    Westerveld T, de Vries AP, Westerveld AT, de Vries AP, van Ballegooij AR (2003) CWI at the TREC-2002 Video Track.. In: The Eleventh Text REtrieval Conference (TREC-2002). Gaithersburg, pp 207–216

  32. 32.

    Wu P, Tretter D (2009) Close & closer: social cluster and closeness from photo collections. In: Proceedings of the 17th ACM international conference on Multimedia, MM ’09, pp 709–712. ACM, New York

    Google Scholar 

  33. 33.

    Xie L, Sundaram H, Campbell M (2008) Event mining in multimedia streams.. In: Proceedings of the IEEE, pp 623–647

  34. 34.

    Zhang L, Chen L, Li M, Zhang H (2003) Automated Annotation of Human Faces in Family Albums. Berkeley, pp 355–358

  35. 35.

    Zhao M, Teo YW, Liu S, Chua T-S, Jain R (2006) Automatic person annotation of family photo album. In: Proceedings of the 5th international conference on Image and Video Retrieval, CIVR’06, pp 163–172. Springer-Verlag, Berlin, Heidelberg

    Google Scholar 

  36. 36.

    Zickler T, Stone Z, Darrell T (2008) Autotagging facebook: Social network context improves photo annotation.. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW ’08, pp 1–8

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Correspondence to Xin Shuai.

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Shuai, X., O’Hare, N., Aiello, L.M. et al. Predicting celebrity attendees at public events using stock photo metadata. Multimed Tools Appl 75, 2145–2167 (2016).

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  • Language model
  • Photo metadata
  • Events attendees prediction
  • Stock photos