DIMINISHED REALITY FOR AR SIMULATION OF DEMOLITION AND REMOVAL OF URBAN OBJECTS
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- YABUKI Nobuyoshi
- 大阪大学 大学院工学研究科 環境・エネルギー工学専攻
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- TANEMURA Takashi
- 大阪大学大学院工学研究科 環境・エネルギー工学専攻
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- FUKUDA Tomohiro
- 大阪大学 大学院工学研究科 環境・エネルギー工学専攻
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- MICHIKAWA Takashi
- 大阪大学 環境イノベーションデザインセンター
Bibliographic Information
- Other Title
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- Diminished Realityを用いた構造物撤去新設時の景観検討AR実現に関する研究
Abstract
Augmented Reality (AR) which extends an environment with virtual objects has been studied extensively and has gained popularity in landscape assessment. However, existing AR approaches cannot correctly simulate views after the demolition and removal of outdoor buildings. To resolve this problem, Diminished Reality (DR) has been paid attention. DR is a technique which can remove the image of an existing object and paste the background image on the area of the diminished object in real time. It is well known that accurate registration of video camera's position and direction is quite difficult in AR or DR if it is used outdoors. On the other hand, a measurement technology of point cloud data by using 3D laser scanner has also been focused. Point cloud data can be measured in a wide-range scale such as a city or a country by using Mobile Mapping System (MMS) which is a laser scanner on a moving vehicle. Considering rapid progress of information technology in recent years, it is expected that we can get point cloud data of any place freely in near future. The registration methods using point cloud data for AR have been studied. Therefore, in this research, a Diminished Reality simulation system using point cloud data was proposed. This system facilitates landscape simulation and assessment of demolition and removal of outdoor buildings beforehand.
Journal
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- Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics)
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Journal of Japan Society of Civil Engineers, Ser. F3 (Civil Engineering Informatics) 70 (2), I_16-I_25, 2014
Japan Society of Civil Engineers
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Details 詳細情報について
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- CRID
- 1390282680332445568
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- NII Article ID
- 130005064280
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- ISSN
- 21856591
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- Text Lang
- ja
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed