JACIII Vol.17 No.6 pp. 890-903
doi: 10.20965/jaciii.2013.p0890


Understanding Geographic Attentions of Crowd from Photographing Information

Yusuke Kubo, Masao Kubo, Hiroshi Sato,
Munetaka Hirano, and Akira Namatame

National Defense Academy of Japan, 1-10-20 Hashirimizu, Yokosuka, Kanagawa 239-0811, Japan

May 20, 2013
September 26, 2013
November 20, 2013
web mining, wisdom of crowds, GIS, social serivice, exif
We propose a framework for sharing photographs that reduces a load on communication network. When interesting events occur, many people take photographs of the events. Collecting photographs of such events and quickly building image database would enable us to share information in real-time more concretely than when using text based methods. However, a simple approach sending all photographs to a server immediately may cause congestion of a network infrastructure. In this paper, we propose a digital photographs classification method based on a main object of a photograph without using pixel information. Our method uses photographing information, that includes information about location and azimuth of a camera. Photographing information is automatically embedded into the photographs when it was taken. Our method determines main objects of photographs (socalled subject) and classifies the photographs based on these subjects. We can suppress congestion because only the best photographs transmitted to a server. In addition, classification accuracy is high because of the effect of collective intelligence. In this paper, we confirmed the effectiveness of our method through a series of experiments using a commercially available digital camera.
Cite this article as:
Y. Kubo, M. Kubo, H. Sato, M. Hirano, and A. Namatame, “Understanding Geographic Attentions of Crowd from Photographing Information,” J. Adv. Comput. Intell. Intell. Inform., Vol.17 No.6, pp. 890-903, 2013.
Data files:
  1. [1] Ministry of Internal Affairs and Communications (Japan), “2011 WHITE PAPER Information and Communications in Japan,” pp. 2-8, 2011.
  2. [2] T. Ichiguchi, “Robust and Usable Media for Communication in a Disaster,” Science and Technology Trends, No.6, pp. 8-20, 2011.
  3. [3] K. Yano, K. Kawakami, and K. Honma, “Evaluation of the Countermeasure for Flaming Problem on the Regional Network Community Service,” IPSJ Journal, Vol.46, No.3, pp. 765-771, 2005.
  4. [4] A. Abe, T. Sasaki, and N. Odashima, “Development and Operational Evaluation of the Groupware Based on Geographical Location Information for Local Community Activities,” IPSJ Journal, Vol.45, No.1, pp. 155-163, 2004.
  5. [5] M. Aoki, S. Yonemura, and K. Shimokura, “Information Sharing System In Disasters using Cellular Phones with GPS,” IPSJ SIG Technical Reports, Vol.2006-ITS-27, pp. 163-168, 2006.
  6. [6] Y. Kuwata, A. Shinjo, H. Ohtani, and U. Inoue, “A GIS-based Realtime Disaster Information Sharing System,” IPSJ Journal, Vol.43, No.11, pp. 3419-3428, 2002.
  7. [7] A. Shinjo, and S. Yoshida, “Data transmission methodology for disaster information in unstable network,” VRSJ, Vol.8, No.1, pp. 19-25, 2003.
  8. [8] H. Doizaki, and T. Ando, and A. Kanai, “A Study on an Algorithm to Search Photograph with Location and Attitude Information,” IPSJ SIG Technical Reports, Vol.2010-GN-74, No.8, pp. 1-6, 2010.
  9. [9] H. Fujita, M. Arikawa, and K. Okamura, “Three-Dimensional Real Space Mapping of Photographs with Precise Spatial Metadata,” IEICE Trans. A, Vol.J87-A, No.1, pp. 120-131, 2004.
  10. [10] Standard of the Camera & Imaging Products Association, “Exchangeable image file format for digital still camera : Exif Version 2.3,” Standard of the Camera & Imaging Products Association,, 2010.
  11. [11] T. Ando, H. Doizaki, and A. Kanai, “A Study on System to Search Photograph with Location and Attitude Information,” IPSJ SIG Technical Reports, Vol.2010-GN-74, No.7, pp. 1-6, 2010.
  12. [12] T. Sakaki, M. Ozaki, and Y. Matsuo, “Earthquake shakes Twitter users: real-time event detection by social sensors,” Proc. the 19th Int. Conf. on World Wide Web, pp. 851-860, ACM, 2010.
  13. [13] M. Kumano, M. Koseki, K. Ono, and M. Kimura, “Extracing Hot Photo-spots from Geotagged Photographs with Timestamps,” IPSJ Journal, Vol.5, No.3, pp. 41-53, 2012.
  14. [14] M. Kubo, S. Nakayama, and H. Sato, “Collective Discovery of Geographic Locations of Frequently Photographed Objects Only using the Metadata of Digital Photographs,” Procedia Computer Science, Vol.10, pp. 625-633, 2012.
  15. [15] M. Shirai, M. Hirota, S. Yokoyama, N. Fukuta, and H. Ishikawa, “A System for Reproducing Multi-viewpoint Landmarks using Geotagged Photos,” Proc. DEIM Forum 2012, 2012.
  16. [16] Y. Kubo, M. Kubo, H. Sato, and A. Namatame, “Understanding Geographic Attentions of Crowd from Only Metadata of Photo Colletions,” Proc. the 16th Asia Pacific Symp. on Intelligent and Evolutionary Systems, pp. 71-81, 2012.
  17. [17] Christopher M. Bishop and others, “Pattern recognition and machine learning,” Springer New York, pp. 541-542, 2006.

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