关键点检测的复杂建筑物模型自动重建
An automated approach for complex shape building reconstruction with key point detection
- 2014年18卷第6期 页码:1237-1246
纸质出版日期: 2014
DOI: 10.11834/jrs.20144081
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纸质出版日期: 2014 ,
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[1]李鹏程,邢帅,徐青,周杨,刘志青,张艳,耿迅.关键点检测的复杂建筑物模型自动重建[J].遥感学报,2014,18(06):1237-1246.
LI Pengcheng, XING Shuai, XU Qing, et al. An automated approach for complex shape building reconstruction with key point detection[J]. Journal of Remote Sensing, 2014,18(6):1237-1246.
利用机载Li DAR点云数据进行建筑物重建是当今摄影测量与遥感领域的一个热点问题
特别是复杂形状建筑物模型的精确自动构建一直是一个难题。本文提出一种基于关键点检测的复杂建筑物模型自动重建方法
采用RANSAC法与距离法相结合的分割方法自动提取建筑物屋顶各个平面的点云
并利用Alpha Shape算法提取出各个平面的精确轮廓
根据屋顶平面之间的空间拓扑关系分析建筑物的公共交线特征
在此特征约束下对提取的初始关键点进行修正
最终重建出精确的建筑物3维模型。选取不同类型复杂建筑物与包含复杂建筑物的城市区域点云进行实验
结果表明该算法具有较强实用价值。
Currently
automated reconstruction of buildings from data acquired by airborne Li DAR has been an important research topic in photogrammetry
especially for the precise reconstruction of complex buildings. Given the various and complex structures of buildings and the discrete distribution of laser data
automatically reconstructing complex buildings using airborne Li DAR data is complex. Certain methods are only suitable for buildings with simple structure
whereas some methods reconstruct the building models with the aid of other data source
such as remote sensing images and ground plans. Hence
this study proposed an automated approach for complex shape building reconstruction based on key point detection that only makes use of airborne Li DAR point cloud to solve the problems on the automated reconstruction of complex buildings. The point clouds of different roof planes are extracted automatically by combining RANSAC segmentation and space segmentation. For each plane
the exact contour is picked up using the Alpha Shape algorithm. Public intersection line features are determined by topological relation of these planes
which will help correcting the initial key points. Finally
the precise building model is obtained. Detection of the key points is important for our method
which contains extraction of initial key points
judgment of topological relation of planes
correction of key points
and model reconstruction. During judgment of topological relation of planes
three pubic intersection line features should be determined
namely
public line segment
public radial
and public line. The final key points are then calculated correctly according to these restraints. Two different types of buildings and one urban area were chosen to verify our method. Building 1 is composed of many horizontal roofs with different height levels
without intersection among those roof planes; whereas Building 2 consists of some gable roofs with relative more complex relationship. The experimental results showed that RANSAC and space combined segmentation is fantastic
the initial key points present the sketchy structure of the building roof
the vectorized roof models show the public intersection line features reasonably
and the final reconstructed building models fit the remote sensing images well. To further validate the effectiveness of our approach
the same two buildings were processed using Terra Solid and the models were compared with our results. The comparison proved that the accuracy of our approach is close to that Terra Solid. The selected urban area contains flat roof buildings
gable roof buildings
L shape buildings
hipped buildings
and complex structure buildings c ombined with the above typical shapes. Successful reconstruction of this area proves that our approach is suitable to urban area point cloud with complex shape buildings and is effective and practicable. Our approach realized the automated reconstruction of complex shape building models by point cloud segmentation
contour extraction
and key point detection. Experimental results of different types of buildings and one urban area showed that:( 1) Our method can reconstruct complex-shaped buildings effectively;( 2) Compared with TerraSolid the reconstructed results
the accuracy of our method is close to that of Terra Solid and is valuable;( 3) The method is restricted by point cloud segmentation. If the threshold in the segmentation is rigorous
some roof plane point clouds would be lost
which would have side effect on the final reconstruction results.
建筑物重建机载Li DAR点云分割轮廓提取关键点检测
building reconstructionairborne Li DARpoint cloud segmentationcontour extractionkey points detection
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