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실내 포인트 클라우드 데이터 Downsampling의 Trade-off 분석을 통한 기초 연구
강남우 ( Kang Nam-woo ),오상민 ( Oh Sang-min ),류민우 ( Ryu Min-woo ),정용일 ( Jung Yong-gil ),조훈희 ( Cho Hun-hee ) 한국건축시공학회 2020 한국건축시공학회 학술발표대회 논문집 Vol.20 No.1
As the capacity of the 3d scanner developed, the reverse engineering using the 3d scanner is emphasized in the construction industry to obtain the 3d geometric representation of buildings. However, big size of the indoor point cloud data acquired by the 3d scanner restricts the efficient process in the reverse engineering. In order to solve this inefficiency, several pre-processing methods simplifying and denoising the raw point cloud data by the rough standard are developed, but these non-standard methods can cause the inaccurate recognition and removal the key-points. This paper analyzes the correlation between the accuracy of wall recognition and the density of the data, thus proposes the proper method for the raw point cloud data. The result of this study could improve the efficiency of the data processing phase in the reverse engineering for indoor point cloud data.