Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

A multi-criteria context-sensitive approach for social image collection summarization

  • Published:
Sādhanā Aims and scope Submit manuscript

Abstract

Recent increase in the number of digital photos in the content sharing and social networking websites has created an endless demand for techniques to analyze, navigate, and summarize these images. In this paper, we focus on image collection summarization. Earlier methods in image collection summarization consider representativeness and diversity criteria while recent ones also consider other criteria such as image quality, aesthetic or appeal. In this paper, we propose a multi-criteria context-sensitive approach for social image collection summarization. In the proposed method, two different sets of features are combined while each one looks at different criteria for image collection summarization: social attractiveness features and semantic features. The first feature set considers different aspects that make an image appealing such as image quality, aesthetic, and emotion to create attractiveness score for input images while the second one covers semantic content of images and assigns semantic score to them. We use social network infrastructure to identify attractiveness features and domain ontology for extracting ontology features. The final summarization is provided by integrating the attractiveness and semantic features of input images. The experimental results on a collection of human generated summaries on a set of Flickr images demonstrate the effectiveness of the proposed image collection summarization approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Tschiatschek S, Iyer R K, Wei H and Bilmes J A 2014 Learning Mixtures of Submodular Functions for Image Collection Summarization. In: Advances in Neural Information Processing Systems, pp. 1413–1421

  2. Simon I A, Noah S and Seitz S M 2007 Scene summarization for online image collections. In: IEEE 11th International Conference on Computer Vision (ICCV 2007)

  3. Rudinac S, Larson M and Hanjalic A, 2013 Learning crowdsourced user preferences for visual summarization of image collections. IEEE Trans. Multimed. 15(6): 1231–1243

    Article  Google Scholar 

  4. Yang C, Shen J, Peng J and Fan J 2013 Image collection summarization via dictionary learning for sparse representation. Pattern Recognit. 46: 948–961

    Article  Google Scholar 

  5. Jia Y, Wang J, Zhang C and Hua X S 2008 Finding image exemplars using fast sparse affinity propagation. In: Proceedings of the 16th ACM International Conference on Multimedia

  6. Zhao Y, Hong R and Jiang J 2016 Visual summarization of image collections by fast RANSAC. Neurocomputer 172: 48–52

    Article  Google Scholar 

  7. Crandall D J, Backstrom L, Huttenlocher C and Kleinberg J 2009 Mapping the world’s photos. In: Proceedings of the 18th International Conference on World Wide Web

  8. Jing Y and Baluja S 2008 Visualrank: applying pagerank to large-scale image search. IEEE Trans. Pattern Anal. Mach. Intell. 30(11): 1877–1890

    Article  Google Scholar 

  9. Wang J, Jia L and Hua X-S 2011 Interactive browsing via diversified visual summarization for image search results. Multimed. Syst. 17(5): 379–391

    Article  Google Scholar 

  10. Samani Z R and Moghaddam M E 2016 A knowledge-based semantic approach for image collection summarization. Multimed. Tools Appl. 76(9): 11917–11939

    Article  Google Scholar 

  11. Kennedy L S and Naaman M 2008 Generating diverse and representative image search results for landmarks. In: Proceedings of the 17th International Conference on World Wide Web

  12. Qian X, Lu D, Wang Y, Zhu L, Tang Y Y and Wang M 2017 Image re-ranking based on topic diversity. IEEE Trans. Image Process. 26: 3734–3747

    Article  MathSciNet  Google Scholar 

  13. Camargo J E and González F A 2016 Multimodal latent topic analysis for image collection summarization. Inf. Sci. 328(6): 270–287

    Article  Google Scholar 

  14. Yan Y, Liu G, Wang S, Zhang J and Zheng K 2014 Graph-based clustering and ranking for diversified image search. Multimedia Syst. 3(1): 41–52

    Article  Google Scholar 

  15. Li M Zhao C and Tang J 2013 Hybrid image summarization by hypergraph partition. Neurocomputing 119: 41–48

    Article  Google Scholar 

  16. Xu H, Wang J, Hua X S and Li S 2011 Hybrid image summarization. In: Proceedings of the 19th ACM International Conference on Multimedia

  17. Jeong J-W, Hong H-K, Heu J-U, Qasim I and Lee D-H 2012 Visual summarization of the social image collection using image attractiveness learned from social behaviors. In: IEEE International Conference on Multimedia and Expo (ICME), 2012, pp. 538–543

  18. Jaffe A, Naaman M, Tassa T and Davis M 2006 Generating summaries and visualization for large collections of geo-referenced photographs. In: Proceedings of the 8th ACM international workshop on Multimedia information retrieval

  19. Fang H, Lu W, Wu F, Zhang Y, Shang X, Shao J et al 2015 Topic aspect-oriented summarization via group selection. Neurocomputing 149: 1613–1619

    Article  Google Scholar 

  20. Shen X and Tian X 2016 Multi-modal and multi-scale photo collection summarization. Multimed. Tools Appl. 75: 2527–2541

    Article  Google Scholar 

  21. Brindha N and Visalakshi P 2017 Bridging semantic gap between high-level and low-level features in content-based video retrieval using multi-stage ESN–SVM classifier. Sādhanā 42(1): 1–10

    MathSciNet  MATH  Google Scholar 

  22. Lu Z, Lin Y-R, Huang X, Xiong N and Fang Z 2017 Visual topic discovering, tracking and summarization from social media streams. Multimed. Tools Appl. 76(8): 10855–10879

    Article  Google Scholar 

  23. Lidon A, Bolaños M, Dimiccoli M, Radeva P, Garolera M and Giro-i-Nieto X 2017 Semantic summarization of egocentric photo stream events. In: Proceedings of the 2nd Workshop on Lifelogging Tools and Applications, pp. 3–11

  24. Osmanlıoğlu Y, Shakibajahromi B and Shokoufandeh A 2017 Autonomous Multi-camera Tracking Using Distributed Quadratic Optimization. In: International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition, 2017, pp. 175–188

  25. Samani Z R and Shamsfard M 2018 The State of the Art in Developing Fuzzy Ontologies: A Survey, arXiv preprint arXiv:1805.02290

  26. Samani Z R and Shamsfard M 2011 A fuzzy ontology model for qualitative spatial reasoning. In: 6th International Conference on Computer Sciences and Convergence Information Technology (ICCIT), 2011, pp. 1–6

  27. Latha T K K 2015 Optimization of sparse dictionary model for multimodal image summarization using firefly algorithm. Int J. Appl. Eng. Res. 10(55): 1896–1901

    Google Scholar 

  28. Kardaani M and Moghadam M E 2015 Attractive social image extraction based on users’ social behaviors. In: 9th Iranian Conference on Machine Vision and Image Processing (MVIP). 2015, IEEE

  29. van Zwol R, Rae A and Garcia Pueyo L 2010 Prediction of favourite photos using social, visual, and textual signals. In: Proceedings of the 18th ACM International Conference on Multimedia. ACM

  30. San Pedro J and Siersdorfer S Ranking and classifying attractiveness of photos in folksonomies. In: Proceedings of the 18th International Conference on World wide web. 2009, ACM

  31. Geng B, Yang L, Xu C, Hua X-S and Li S 2011 The role of attractiveness in web image search. In: Proceedings of the 19th ACM International Conference on Multimedia. ACM

  32. Abdollahpour Z, Samani Z R and Moghaddam M E 2015 Image classification using ontology based improved visual words. In: 2015 23rd Iranian Conference on Electrical Engineering. IEEE

  33. Chatfield K, Lempitsky V, Vedaldi A and Zisserman A 2011 The devil is in the details: an evaluation of recent feature encoding methods. In: J Hoey, M Stephen and T Emanuele (Eds) Proceedings of the British Machine Vision Conference, BMVA Press, 2011, pp. 76.1–76.12

  34. Barman S, Chattopadhyay S, Samanta D, Bag S and Show G 2014 An efficient fingerprint matching approach based on minutiae to minutiae distance using indexing with effectively lower time complexity. In: Information Technology (ICIT), 2014 International Conference on. 2014, IEEE.

  35. Malik F and Baharudin B 2013 Analysis of distance metrics in content-based image retrieval using statistical quantized histogram texture features in the DCT domain. J. King Saud Univ. Comput. Inf. Sci. 25(2): 207–218

  36. Qian G, Sural S and Pramanik S 2002 A comparative analysis of two distance measures in color image databases. In: Image Processing. 2002. Proceedings. 2002 International Conference on. 2002, IEEE

  37. Singh S, Bag S and Jenamani M 2015 Relative similarity based approach for improving aggregate recommendation diversity. In: India Conference (INDICON), 2015 Annual IEEE. IEEE

  38. Li Y and Merialdo B 2010 VERT: automatic evaluation of video summaries. In: Proceedings of the International Conference on Multimedia. ACM

Download references

Author information

Authors and Affiliations

  1. Faculty of computer Science and Engineering, Shahid Beheshti University, GC, Tehran, 1983969411, Iran

    Zahra Riahi Samani & Mohsen Ebrahimi Moghaddam

Authors
  1. Zahra Riahi Samani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohsen Ebrahimi Moghaddam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohsen Ebrahimi Moghaddam.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Samani, Z.R., Moghaddam, M.E. A multi-criteria context-sensitive approach for social image collection summarization. Sādhanā 43, 143 (2018). https://doi.org/10.1007/s12046-018-0908-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12046-018-0908-9

Keywords

Search

Navigation