지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.12
- 수록면
- 83 - 90 (8page)
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초록· 키워드
오류제보하기
The game environment similar to the real environment increases the user's sense of immersion. Especially in the real world, buildings are an important factor in giving users a sense of realism. Real environmental data such as satellite image, aerial image, and 360° image have already been digitized and are being serviced like Google Street View or Kakao Road View, but there is no special reprocessing.
Constructing the world from 3D models rather than images is already a work in progress. However, the work done by Google and others mainly uses aerial images as textures for their models, which are highly distorted and have low resolution. In this study, an independent building mesh was created in 3D space by extracting street images and metadata from the existing 360° street image service to compose a map where users move and interact. Street views are placed in a 3D space using TM coordinates so that appropriate street view is applied according to the user's movement. We analyzed the depth data to apply depth to a spherical screen projected into street view, separated the buildings from the background in street view, and projected each building onto a separate vertical plane. Each building was also rotated to maintain its initial orientation following the user, giving the impression of continuity of the building plane in transitions between street views. This study aims to increase the value of existing digital data by reprocessing it so that it can be used in various fields.
목차
등록된 정보가 없습니다.
참고문헌 (12)
참고문헌 신청
차명희 / 2012 / 게임 환경의 건축물 배경 맵 모델 연구 / 한국컴퓨터게임학회논문지 25(4):205~212
Xiaojiang Li / 2018 / Quantifying the shade provision of street trees in urban landscape : A case study in Boston, USA, using Google Street View / Landscape and Urban Planning 169:81~91
Ye, Yu / 2019 / The visual quality of streets : A human-centred continuous measurement based on machine learning algorithms and street view images / Environment and Planning B: Urban Analytics and City Science 46(8):1439~1457
Kang, Jian / 2018 / Building instance classification using street view images / ISPRS Journal of photogrammetry and remote sensing 145:44~59
N. Bruno / 2019 / ACCURACY ASSESSMENT OF 3D MODELS GENERATED FROM GOOGLE STREET VIEW IMAGERY / International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences
Xiaojiang Li / 2018 / Quantifying the shade provision of street trees in urban landscape : A case study in Boston, USA, using Google Street View / Landscape and Urban Planning 169:81~91
Ye, Yu / 2019 / The visual quality of streets : A human-centred continuous measurement based on machine learning algorithms and street view images / Environment and Planning B: Urban Analytics and City Science 46(8):1439~1457
Kang, Jian / 2018 / Building instance classification using street view images / ISPRS Journal of photogrammetry and remote sensing 145:44~59
N. Bruno / 2019 / ACCURACY ASSESSMENT OF 3D MODELS GENERATED FROM GOOGLE STREET VIEW IMAGERY / International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences
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