Automatic extraction and reconstruction of a 3D wireframe of an indoor scene from semantic point clouds  

作　　者：Junyi Wei Hangbin Wu Han Yue Shoujun Jia Jintao Li Chun Liu 

机构地区：[1]College of Surveying and Geo-informatics,Tongji University,Shanghai,People's Republic of China

出　　处：《International Journal of Digital Earth》2023年第1期3239-3267,共29页国际数字地球学报（英文）

基　　金：supported by the National Key Research and Development Program of China(Grant No.2021YFB2501103);the National Science Foundation of China(Grant No.42271429 and 42130106);the Key Research and Development Projects of Shanghai Science and Technology Commission(Grant No.21DZ1204103).

摘　　要：Accurate indoor 3D models are essential for building administration and applications in digital city construction and operation.Developing an automatic and accurate method to reconstruct an indoor model with semantics is a challenge in complex indoor environments.Our method focuses on the permanent structure based on a weak Manhattan world assumption,and we propose a pipeline to reconstruct indoor models.First,the proposed method extracts boundary primitives from semantic point clouds,such as floors,walls,ceilings,windows,and doors.The primitives of the building boundary,are aligned to generate the boundaries of the indoor scene,which contains the structure of the horizontal plane and height change in the vertical direction.Then,an optimization algorithm is applied to optimize the geometric relationships among all features based on their categories after the classification process.The heights of feature points are captured and optimized according to their neighborhoods.Finally,a 3D wireframe model of the indoor scene is reconstructed based on the 3D feature information.Experiments on three different datasets demonstrate that the proposed method can be used to effectively reconstruct 3D wireframe models of indoor scenes with high accuracy.

关 键 词：Point cloud primitive extraction semantic optimization indoor model reconstruction 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]