Research progress of building reconstruction via airborne point clouds

被引：0
|
作者：
Du J. [1 ]
Chen D. [2 ]
Zhang Z. [3 ]
Zhang L. [4 ]
机构：
[1] School of Geodesy and Geomatics, Wuhan University, Wuhan
[2] College of Civil Engineering, Nanjing Forestry University, Nanjing
[3] College of Resource Environment and Tourism, Capital Normal University, Beijing
[4] State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing
来源：
Yaogan Xuebao/Journal of Remote Sensing | 2019年 / 23卷 / 03期
基金：
中国国家自然科学基金;
关键词：
3D building reconstruction; Airborne LiDAR; Airborne point clouds; Building geometric models; Review;
D O I：
10.11834/jrs.20188199
中图分类号：
学科分类号：
摘要：
Creating photorealistic building models from large-scale airborne point clouds is an important aspect of urban modeling. Given the complexity of airborne points (i.e., noise, outliers, occlusions, and irregularities) and diversified architectures in the real world, the problems associated with the creation of photorealistic building models pose great challenges, but these problems are not comprehensively addressed by most of the state-of-the-art methods. In this research, intelligent algorithms are developed to create large-scale LoD3 building models with accurate geometry, correct topology, and abundant semantics. The developed algorithms can enhance the abstraction/representation of building point clouds. First, from the perspective of building model mechanism, modeling algorithms are divided into five categories, each of which is reviewed and analyzed in depth. Then, the common problems are determined, and their possible solutions are given accordingly. Finally, the possible directions of future building reconstruction are predicted on the basis of airborne point clouds. We aim to provide beneficial inspiration and relevant references to enhance building modeling theories, develop more intelligent modeling algorithms, and create high-quality building models. © 2019, Science Press. All right reserved.
引用
收藏
页码：374 / 391
页数：17
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