Pano UMECHIKA: A crowded underground city panoramic view system

Ismail Arai, Maiya Hori, Norihiko Kawai, Yohei Abe, Masahiro Ichikawa, Yusuke Satonaka, Tatsuki Nitta, Tomoyuki Nitta, Harumitsu Fujii, Masaki Mukai, Soichiro Horimi, Koji Makita, Masayuki Kanbara, Nobuhiko Nishio, Naokazu Yokoya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationDistributed Computing and Artificial Intelligence
Subtitle of host publication7th International Symposium
EditorsAndre Ponce de Leon F Carvalho, Sara Rodriguez Gonzalez, Juan Paz Santana, Juan Corchado Rodriguez
Number of pages8
Publication statusPublished - 2010
Externally publishedYes

Publication series

NameAdvances in Intelligent and Soft Computing
ISSN (Print)1867-5662

All Science Journal Classification (ASJC) codes

  • Computer Science(all)


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