Abstract
The fast development of Internet and personal electronic devices has led to a dramatic growth of landmark images available on social media sites such as Flickr. With their informative and attractive content, landmark images have received considerable attention in multimedia research community. Most of existing methods focus on exploring landmark images by their spatial distribution, while largely ignoring the temporal aspect. Through digging the temporal information in the shared images, we can reveal the series of historical moments of landmarks, which could be useful for social studies and attractive to tourists. In this paper, we propose a scheme named Landmark Timeline Construction(LTC), which automatically mines and selects diverse images on historical events of a landmark simply from Flickr. In our scheme, Time Interval Selection Algorithm is proposed to handle the limitation of the existing methods on the fixed time interval by assigning the optimal ones to different tags. The experimental results demonstrate the effectiveness of our methods.
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References
Chen, C.C., Chen, Y.-T., Sun, Y., Chen, M.C.: Life Cycle Modeling of News Events Using Aging Theory. In: Lavrač, N., Gamberger, D., Todorovski, L., Blockeel, H. (eds.) ECML 2003. LNCS (LNAI), vol. 2837, pp. 47–59. Springer, Heidelberg (2003)
Chen, K., Luesukprasert, L., Chou, S., et al.: Hot topic extraction based on timeline analysis and multidimensional sentence modeling. IEEE Transactions on Knowledge and Data Engineering 19(8), 1016–1025 (2007)
Chen, L., Roy, A.: Event detection from flickr data through wavelet-based spatial analysis. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management, pp. 523–532. ACM (2009)
Crandall, D., Backstrom, L., Huttenlocher, D., Kleinberg, J.: Mapping the world’s photos. In: Proceedings of the 18th International Conference on World Wide Web, pp. 761–770. ACM (2009)
Fellbaum, C.: Wordnet. In: Theory and Applications of Ontology: Computer Applications, pp. 231–243 (2010)
He, J., Li, M., Zhang, H., Tong, H., Zhang, C.: Manifold-ranking based image retrieval. In: Proceedings of the 12th Annual ACM International Conference on Multimedia, pp. 9–16. ACM (2004)
Kennedy, L., Naaman, M.: Generating diverse and representative image search results for landmarks. In: Proceeding of the 17th International Conference on World Wide Web, pp. 297–306. ACM (2008)
Kennedy, L., Naaman, M., Ahern, S., Nair, R., Rattenbury, T.: How flickr helps us make sense of the world: context and content in community-contributed media collections. In: Proceedings of the 15th International Conference on Multimedia, pp. 631–640. ACM (2007)
Rattenbury, T., Good, N., Naaman, M.: 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, pp. 103–110. ACM (2007)
Rudinac, S., Hanjalic, A., Larson, M.: Finding representative and diverse community contributed images to create visual summaries of geographic areas. In: Proceedings of the 19th ACM International Conference on Multimedia, pp. 1109–1112. ACM (2011)
Wang, M., Yang, K., Hua, X., Zhang, H.: Towards a relevant and diverse search of social images. IEEE Transactions on Multimedia 12(8), 829–842 (2010)
Weyand, T., Leibe, B.: Discovering favorite views of popular places with iconoid shift. In: 2011 IEEE International Conference on Computer Vision, ICCV, pp. 1132–1139. IEEE (2011)
Yang, D., Powers, D.: Measuring semantic similarity in the taxonomy of wordnet. In: Proceedings of the Twenty-Eighth Australasian Conference on Computer Science, vol. 38, pp. 315–322. Australian Computer Society, Inc. (2005)
Yang, Y., Pierce, T., Carbonell, J.: A study of retrospective and on-line event detection. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 28–36. ACM (1998)
Zheng, Y., Zhao, M., Song, Y., Adam, H., Buddemeier, U., Bissacco, A., Brucher, F., Chua, T., Neven, H.: Tour the world: building a web-scale landmark recognition engine. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 1085–1092. IEEE (2009)
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Min, W., Bao, BK., Xu, C. (2012). What Happened Near Big Ben: Event-Driven Landmark Mining from Flickr. In: Lin, W., et al. Advances in Multimedia Information Processing – PCM 2012. PCM 2012. Lecture Notes in Computer Science, vol 7674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34778-8_72
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DOI: https://doi.org/10.1007/978-3-642-34778-8_72
Publisher Name: Springer, Berlin, Heidelberg
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