TY - JOUR AU - Korawit Pleansamai, AU - Krisada Chaiyasarn, PY - 2019/04/20 Y2 - 2024/03/29 TI - M-ESTIMATOR SAMPLE CONSENSUS PLANAR EXTRACTION FROM IMAGE-BASED 3D POINT CLOUD FOR BUILDING INFORMATION MODELLING JF - GEOMATE Journal JA - INTERNATIONAL JOURNAL OF GEOMATE VL - 17 IS - 63 SE - Articles DO - UR - https://geomatejournal.com/geomate/article/view/2138 SP - 69-76 AB - <p>Building Information Models (BIMs) are used as an official standard to manage information<br>in the construction industry. Creating a BIM model is still a laborious process, especially in existing<br>buildings, where digital CAD models are often not available. The current process of creation of a BIM model<br>for existing structures generally involves the generation of a geometric model from a 3D point cloud,<br>commonly created by a laser scan, which can be time consuming and expensive. However, image-based 3D<br>modeling techniques are more economical and efficient. In this paper, a 3D point cloud from images and<br>laser scan were used to detect planes using plane detection algorithms based on the M-estimator Sample<br>Consensus (MSAC). The accuracy of 3D point clouds of both techniques was compared using the Iterative<br>Closest Point algorithm. The sample data used in the study was obtained from a laboratory, which contains<br>3D points from many visible planes, such as walls and floors. The MSAC algorithm was applied to detect<br>planes in the 3D point clouds from the image-based and laser scanning techniques. The parameters derived<br>from the plane detection algorithms were subsequently used to create BIM models through the eXtensible<br>Building Information Modeling (xBIM). The proposed plane detection algorithm shows promising results<br>with a low mean square error. These results demonstrate that a BIM model can be created from an imagebased 3D point cloud, which is more convenient and easy to use than the point cloud from a laser scanner.<br><br></p> ER -