Skip to main content

Pano UMECHIKA: A Crowded Underground City Panoramic View System

  • Conference paper
Distributed Computing and Artificial Intelligence


Toward a really useful navigation system, utilizing spherical panoramic photos with maps like Google Street View is efficient. Users expect the system to be available in all areas they go. Conventional shooting methods obtain the shot position from GPS sensor. However, indoor areas are out of GPS range. Furthermore, most urban public indoor areas are crowded with pedestrians. Even if we blur the pedestrians in a photo, the photos with blurring are not useful for scenic information. Thus, we propose a method which simultaneously subtracts pedestrians based on background subtraction method and generates location metadata by manually input from maps. Using these methods, we achieved an underground panoramic view system which displays no pedestrians.

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

Access this chapter

USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
USD 469.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 599.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others


  1. Google Street View,

  2. earthmine,

  3. Nishio, N., Sakamoto, N., Arai, I.: Adjunct Proceedings of Pervasive 2009, pp. 269–272 (2009)

    Google Scholar 

  4. Kawai, N., Machikita, K., Sato, T., Yokoya, N.: Proc. Asian Conf. on Computer Vision (ACCV(2)), pp. 359–370 (2009)

    Google Scholar 

  5. Cheng, Y., Chawathe, Y., LaMarca, A., Krumm, J.: Proceeings of Mobisys 2005, pp. 233–245 (2005)

    Google Scholar 

  6. Harter, A., Hopper, A., Steggles, P., Ward, A., Webster, P.: The Fifth Annual ACM/IEEE International Conference on Mobile Computing and Networking, MOBICOM 1999, pp. 59–68 (1999)

    Google Scholar 

  7. Yahoo! Maps (JAPAN),

  8. O3D,

  9. Lowe, D.G.: International Journal of Computer Vision 60(2), 91 (2004)

    Google Scholar 

  10. Bay, H., Ess, A., Tuytelaars, T., Gool, L.V.: Computer Vision and Image Understanding (CVIU) 110(3), 346 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations


Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Arai, I. et al. (2010). Pano UMECHIKA: A Crowded Underground City Panoramic View System. In: de Leon F. de Carvalho, A.P., Rodríguez-González, S., De Paz Santana, J.F., Rodríguez, J.M.C. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 79. Springer, Berlin, Heidelberg.

Download citation

  • DOI:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14882-8

  • Online ISBN: 978-3-642-14883-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics