Change detection of multi-temporal oblique aerial images

Yun An Chen, Jyun Ping Jhan, Jiann-Yeou Rau

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

Abstract

Due to the rapidly urbanization development, to monitor the change of city environment is more important for urban land resource management. Different to traditional vertical aerial image (VAI), the oblique aerial image (OAI) shows more stereoscopic for manually recognition, and has more information practically on building façade. Various studies has investigated the potential of its applications, such as building seismic damage assessment, performing large area mapping by multi-views image mosaicking, and building objects extraction and classification. In this study, both VAIs and OAIs are collected from airborne and UAV platform in two different periods for change detection purpose. Through photogrammetry techniques including orientation reconstruction and dense image matching, the colored high density 3D point clouds of first period data are generate from both vertical and oblique images. A virtual image has same viewpoint of one selected second period master image can thus be generated by considering hidden points and back-projection. Then, a feature matching scheme is performed on virtual image and master image to find the different area.

Original languageEnglish
Title of host publicationACRS 2015 - 36th Asian Conference on Remote Sensing
Subtitle of host publicationFostering Resilient Growth in Asia, Proceedings
PublisherAsian Association on Remote Sensing
Publication statusPublished - 2015
Event36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015 - Quezon City, Metro Manila, Philippines
Duration: 2015 Oct 242015 Oct 28

Other

Other36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015
CountryPhilippines
CityQuezon City, Metro Manila
Period15-10-2415-10-28

Fingerprint

Antennas
Image matching
Photogrammetry
Unmanned aerial vehicles (UAV)

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Chen, Y. A., Jhan, J. P., & Rau, J-Y. (2015). Change detection of multi-temporal oblique aerial images. In ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings Asian Association on Remote Sensing.
Chen, Yun An ; Jhan, Jyun Ping ; Rau, Jiann-Yeou. / Change detection of multi-temporal oblique aerial images. ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings. Asian Association on Remote Sensing, 2015.
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title = "Change detection of multi-temporal oblique aerial images",
abstract = "Due to the rapidly urbanization development, to monitor the change of city environment is more important for urban land resource management. Different to traditional vertical aerial image (VAI), the oblique aerial image (OAI) shows more stereoscopic for manually recognition, and has more information practically on building fa{\cc}ade. Various studies has investigated the potential of its applications, such as building seismic damage assessment, performing large area mapping by multi-views image mosaicking, and building objects extraction and classification. In this study, both VAIs and OAIs are collected from airborne and UAV platform in two different periods for change detection purpose. Through photogrammetry techniques including orientation reconstruction and dense image matching, the colored high density 3D point clouds of first period data are generate from both vertical and oblique images. A virtual image has same viewpoint of one selected second period master image can thus be generated by considering hidden points and back-projection. Then, a feature matching scheme is performed on virtual image and master image to find the different area.",
author = "Chen, {Yun An} and Jhan, {Jyun Ping} and Jiann-Yeou Rau",
year = "2015",
language = "English",
booktitle = "ACRS 2015 - 36th Asian Conference on Remote Sensing",
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Chen, YA, Jhan, JP & Rau, J-Y 2015, Change detection of multi-temporal oblique aerial images. in ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings. Asian Association on Remote Sensing, 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015, Quezon City, Metro Manila, Philippines, 15-10-24.

Change detection of multi-temporal oblique aerial images. / Chen, Yun An; Jhan, Jyun Ping; Rau, Jiann-Yeou.

ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings. Asian Association on Remote Sensing, 2015.

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

TY - GEN

T1 - Change detection of multi-temporal oblique aerial images

AU - Chen, Yun An

AU - Jhan, Jyun Ping

AU - Rau, Jiann-Yeou

PY - 2015

Y1 - 2015

N2 - Due to the rapidly urbanization development, to monitor the change of city environment is more important for urban land resource management. Different to traditional vertical aerial image (VAI), the oblique aerial image (OAI) shows more stereoscopic for manually recognition, and has more information practically on building façade. Various studies has investigated the potential of its applications, such as building seismic damage assessment, performing large area mapping by multi-views image mosaicking, and building objects extraction and classification. In this study, both VAIs and OAIs are collected from airborne and UAV platform in two different periods for change detection purpose. Through photogrammetry techniques including orientation reconstruction and dense image matching, the colored high density 3D point clouds of first period data are generate from both vertical and oblique images. A virtual image has same viewpoint of one selected second period master image can thus be generated by considering hidden points and back-projection. Then, a feature matching scheme is performed on virtual image and master image to find the different area.

AB - Due to the rapidly urbanization development, to monitor the change of city environment is more important for urban land resource management. Different to traditional vertical aerial image (VAI), the oblique aerial image (OAI) shows more stereoscopic for manually recognition, and has more information practically on building façade. Various studies has investigated the potential of its applications, such as building seismic damage assessment, performing large area mapping by multi-views image mosaicking, and building objects extraction and classification. In this study, both VAIs and OAIs are collected from airborne and UAV platform in two different periods for change detection purpose. Through photogrammetry techniques including orientation reconstruction and dense image matching, the colored high density 3D point clouds of first period data are generate from both vertical and oblique images. A virtual image has same viewpoint of one selected second period master image can thus be generated by considering hidden points and back-projection. Then, a feature matching scheme is performed on virtual image and master image to find the different area.

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M3 - Conference contribution

BT - ACRS 2015 - 36th Asian Conference on Remote Sensing

PB - Asian Association on Remote Sensing

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Chen YA, Jhan JP, Rau J-Y. Change detection of multi-temporal oblique aerial images. In ACRS 2015 - 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, Proceedings. Asian Association on Remote Sensing. 2015