AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGES
The city of Seoul has selected Sewoon market building and its surrounding district as part of the urban regeneration zone, and currently has been promoting the project. To monitor results of the project regularly, the city has been trying to utilize a 3 dimension model of the area. In the case of bu...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2020-08-01
|
Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/63/2020/isprs-archives-XLIII-B2-2020-63-2020.pdf |
id |
doaj-711ca288ebed4478b8108457573a92d4 |
---|---|
record_format |
Article |
spelling |
doaj-711ca288ebed4478b8108457573a92d42020-11-25T03:46:03ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B2-2020636810.5194/isprs-archives-XLIII-B2-2020-63-2020AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGESK. Park0S. Ham1I. Lee2Dept. of Geoinformatics, University of Seoul, Seoul, Republic of KoreaDept. of Geoinformatics, University of Seoul, Seoul, Republic of KoreaDept. of Geoinformatics, University of Seoul, Seoul, Republic of KoreaThe city of Seoul has selected Sewoon market building and its surrounding district as part of the urban regeneration zone, and currently has been promoting the project. To monitor results of the project regularly, the city has been trying to utilize a 3 dimension model of the area. In the case of buildings placed in narrow alleyways in the district, however, it is limited to generate 3D model of the buildings due to some factors. Therefore, in this study, a 3D model of façade of the building was created, using a RTK drone and action camera only. First method is to estimate of location of conjugate points using Structure from Motion, after setting conjugate points between images of the drone. Second method is to georeference action camera images by setting drone images as the reference images itself without the process of estimating location of the conjugate points. As a result of preliminary experiments to verify the two methods, the error of each method did not exceed a maximum of 0.030 m. Based on the result, we created 3D models of façade of the building in the alleyway, which is located at the intersection of Donhwamoon-ro 2 gil and Jong-ro 24 gil, and calculated absolute distance between the models. And the comparison showed that the difference was about 0.010 m on average.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/63/2020/isprs-archives-XLIII-B2-2020-63-2020.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
K. Park S. Ham I. Lee |
spellingShingle |
K. Park S. Ham I. Lee AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGES The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
K. Park S. Ham I. Lee |
author_sort |
K. Park |
title |
AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGES |
title_short |
AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGES |
title_full |
AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGES |
title_fullStr |
AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGES |
title_full_unstemmed |
AUTOMATIC GEOREFERNCING OF CLOSE-RANGE FAÇADE IMAGES ACQUIRED IN AN NARROW AND LONG ALLEYWAY USING RTK DRONE IMAGES |
title_sort |
automatic georeferncing of close-range façade images acquired in an narrow and long alleyway using rtk drone images |
publisher |
Copernicus Publications |
series |
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
1682-1750 2194-9034 |
publishDate |
2020-08-01 |
description |
The city of Seoul has selected Sewoon market building and its surrounding district as part of the urban regeneration zone, and currently has been promoting the project. To monitor results of the project regularly, the city has been trying to utilize a 3 dimension model of the area. In the case of buildings placed in narrow alleyways in the district, however, it is limited to generate 3D model of the buildings due to some factors. Therefore, in this study, a 3D model of façade of the building was created, using a RTK drone and action camera only. First method is to estimate of location of conjugate points using Structure from Motion, after setting conjugate points between images of the drone. Second method is to georeference action camera images by setting drone images as the reference images itself without the process of estimating location of the conjugate points. As a result of preliminary experiments to verify the two methods, the error of each method did not exceed a maximum of 0.030 m. Based on the result, we created 3D models of façade of the building in the alleyway, which is located at the intersection of Donhwamoon-ro 2 gil and Jong-ro 24 gil, and calculated absolute distance between the models. And the comparison showed that the difference was about 0.010 m on average. |
url |
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2020/63/2020/isprs-archives-XLIII-B2-2020-63-2020.pdf |
work_keys_str_mv |
AT kpark automaticgeoreferncingofcloserangefacadeimagesacquiredinannarrowandlongalleywayusingrtkdroneimages AT sham automaticgeoreferncingofcloserangefacadeimagesacquiredinannarrowandlongalleywayusingrtkdroneimages AT ilee automaticgeoreferncingofcloserangefacadeimagesacquiredinannarrowandlongalleywayusingrtkdroneimages |
_version_ |
1724508165316280320 |