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NTIS 바로가기대한원격탐사학회지 = Korean journal of remote sensing, v.34 no.6 pt.1, 2018년, pp.1067 - 1087
김수현 ((주)쓰리디랩스 영상공학연구소) , 이수암 ((주)쓰리디랩스 영상공학연구소)
In a study for LiDAR data based building boundary extraction, usually dense point cloud was used to cluster building rooftop area and extract building outline. However, when we used DSM generated from stereo image matching to extract building boundary, it is not trivial to cluster building roof top ...
핵심어 | 질문 | 논문에서 추출한 답변 |
---|---|---|
기존의 LiDAR 자료 기반의 건물 외곽선 추출 연구에서 건물 외곽선을 추출하는 방법은 무엇인가? | 기존의 LiDAR 자료 기반의 건물 외곽선 추출 연구에서는 고정밀 포인트클라우드를 사용하여 자동으로 건물 지붕 영역을 분류하고 이를 입력자료로 하여 건물 외곽선을 추출했다. 반면에 스테레오 영상 정합을 통해 생성된 DSM은 고정밀 포인트클라우드 자료와 달리 원시 자료인 포인트클라우드에 잡음과 비어있는 격자가 존재하기 때문에 완전한 자동으로 건물 지붕 영역을 분류하는데 어려움이 있다. | |
MBR이란 무엇인가? | MBR은 영역 내에 존재하는 모든 정점을 포함하는임의 방향의 직사각형 중 최소 면적이 있는 직사각형을 의미한다(Freeman and Shapira, 1975; Chaudhuri and Samal, 2007). 단순 직사각형 건물의 MBR 생성은 Habib et al. | |
본 연구에서 개발한 watershed segmentation 기법을 적용한 3차원 외곽선 추출 기법의 특징은 무엇인가? | 따라서 본 논문에서는 스테레오 영상 정합을 통해 생성된 DSM에 사용자 입력을 통한 watershed segmentation 기법을 적용하여 반자동으로 건물의 3차원 외곽선을 추출하는 기법을 제안한다. 제안된 기법은 DSM 내 건물 영역을 표시하는 단순한 마커 정보만을 입력하기 때문에 사용자 입력을 최소화한 방식으로 건물의 3차원 외곽선을 생성할 수 있다. |
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