Detecting building-level changes of a city using street images and a 2D city map

Daiki Tetsuka, Takayuki Okatani

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

1 Citation (Scopus)

Abstract

This paper presents a method for detecting city-scale changes of a city from its street images and a 2D map. Using SfM to reconstruct point cloud of the structures of the city, the method estimates the existence of each building by matching the point cloud with the 3D building structures recovered from the map. There are multiple difficulties, such as inaccuracy of the recovered building structures, large differences in observation and thus in point cloud size of individual buildings, and mutual dependency of building existences due to potential occlusions. To solve these, we develop a model of how point cloud is generated in the sequential processes of SfM, an observation model of a building wall, and a greedy iterative approach to cope with the mutual dependency. We experimentally apply the method to the cities damaged by the tsunami that struck Japan in 2011. The results show the effectiveness of the method.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages349-356
Number of pages8
ISBN (Electronic)9781479966820
DOIs
Publication statusPublished - 2015 Feb 19
Event2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015 - Waikoloa, United States
Duration: 2015 Jan 52015 Jan 9

Publication series

NameProceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015

Other

Other2015 15th IEEE Winter Conference on Applications of Computer Vision, WACV 2015
CountryUnited States
CityWaikoloa
Period15/1/515/1/9

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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