Procedural point cloud modelling in scan-to-BIM and scan-vs-BIM applications: a review
Point cloud processing is an essential task in many applications in the AEC domain, such as
automated progress assessment, quality control and 3D reconstruction. As much of the …
automated progress assessment, quality control and 3D reconstruction. As much of the …
A deep learning-based framework for automated extraction of building footprint polygons from very high-resolution aerial imagery
Accurate building footprint polygons provide essential data for a wide range of urban
applications. While deep learning models have been proposed to extract pixel-based …
applications. While deep learning models have been proposed to extract pixel-based …
Joint learning of contour and structure for boundary-preserved building extraction
Most of the existing approaches to the extraction of buildings from high-resolution
orthoimages consider the problem as semantic segmentation, which extracts a pixel-wise …
orthoimages consider the problem as semantic segmentation, which extracts a pixel-wise …
High-precision detection method for large and complex steel structures based on global registration algorithm and automatic point cloud generation
M Guo, M Sun, D Pan, M Huang, B Yan, Y Zhou, P Nie… - Measurement, 2021 - Elsevier
For extremely large and complicated steel structure buildings, the traditional monitoring
method is inefficient and labor-intensive. However, LiDAR and UAV close-range …
method is inefficient and labor-intensive. However, LiDAR and UAV close-range …
Machine learning-based segmentation of aerial LiDAR point cloud data on building roof
ABSTRACT Three-dimensional (3D) reconstruction of a building can be facilitated by
correctly segmenting different feature points (eg in the form of boundary, fold edge, and …
correctly segmenting different feature points (eg in the form of boundary, fold edge, and …
Effective selection of variable point neighbourhood for feature point extraction from aerial building point cloud data
Existing approaches that extract buildings from point cloud data do not select the
appropriate neighbourhood for estimation of normals on individual points. However, the …
appropriate neighbourhood for estimation of normals on individual points. However, the …
A network for landslide detection using large-area remote sensing images with multiple spatial resolutions
Accurately detecting landslides over a large area with complex background objects is a
challenging task. Research in the area suffers from three drawbacks in general. First, the …
challenging task. Research in the area suffers from three drawbacks in general. First, the …
Indoor–Outdoor Point Cloud Alignment Using Semantic–Geometric Descriptor
Aligning indoor and outdoor point clouds is a challenging problem since the overlapping
area is usually limited, thus resulting in a lack of correspondence features. The windows and …
area is usually limited, thus resulting in a lack of correspondence features. The windows and …
Unsupervised building extraction from multimodal aerial data based on accurate vegetation removal and image feature consistency constraint
Accurate building extraction from remotely sensed data is difficult to perform automatically
because of the complex environments and the complex shapes, colours and textures of …
because of the complex environments and the complex shapes, colours and textures of …
Influence of lidar point cloud density in the geometric characterization of rooftops for solar photovoltaic studies in cities
The use of LiDAR (Light Detection and Ranging) data for the definition of the 3D geometry of
roofs has been widely exploited in recent years for its posterior application in the field of …
roofs has been widely exploited in recent years for its posterior application in the field of …