Abstract
This paper considers the problem of selecting representative photographs for regions in the worldwide dimensions. Selecting and generating such representative photographs for representative regions from large-scale collections would help us understand about local specific objects with a worldwide perspective. We propose a solution to this problem using a large-scale collection of geo-tagged photographs. Our solution firstly extracts the most relevant images by clustering and evaluation on the visual features. Then, based on geographic information of the images, representative regions are automatically detected. Finally, we select and generate a set of representative images for the representative regions by employing the Probabilistic Latent Semantic Analysis (PLSA) modelling. The results show the ability of our approach to generate region-based representative photographs.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Flickr.com, http://www.flickr.com/
Jaffe, A., Naaman, M., Tassa, T., Davis, M.: Generating Summaries and Visualization for Large Collections of Geo-Referenced Photographs. In: Proc. of the 8th ACM SIGMM International Workshop on Multimedia Information Retrieval, pp. 89–98 (2006)
Simon, I., Snavely, N., Seitz, S.M.: Scene Summarization for Online Image Collections. In: Proc. of the 11th IEEE International Conference on Computer Vision (2007)
Kennedy, L., Naaman, M.: Generating Diverse and Representative Image Search Results for Landmarks. In: Proc. of the 17th ACM International Conference on World Wide Web, pp. 297–306 (2008)
Raguram, R., Lazebnik, S.: Computing Iconic Summaries of General Visual Concepts. In: Proc. of IEEE CVPR Workshop on Internet Vision (2008)
Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)
Csurka, G., Bray, C., Dance, C., Fan, L.: Visual Categorization with Bags of Keypoints. In: Proc. of ECCV Workshop on Statistical Learning in Computer Vision, pp. 59–74 (2004)
Hofmann, T.: Unsupervised Learning by Probabilistic Latent Semantic Analysis. Machine Learning 43, 177–196 (2001)
Hafner, J., Sawhney, H.S., Equitz, W., Flickner, M., Niblack, W.: Efficient Color Histogram Indexing for Quadratic Form Distance Functions. IEEE Trans. on Pattern Analysis and Machine Intelligence 17(7), 729–736 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Qiu, B., Yanai, K. (2008). Objects over the World. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_31
Download citation
DOI: https://doi.org/10.1007/978-3-540-89796-5_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89795-8
Online ISBN: 978-3-540-89796-5
eBook Packages: Computer ScienceComputer Science (R0)