3D Laser Point Cloud Data Research Articles

Building facade structure extraction method based on three-dimensional laser point cloud by considering semantic information

ABSTRACT Building facade structures serve as important data support for three-dimensional (3D) building modelling. A building facade structure extraction method based on 3D Laser Point Cloud Data (LPCD) by considering semantic information is proposed. The proposed method mainly involves three steps. First, an improved 3D LPCD semantic segmentation method is introduced to extract and label point clouds as the building structure and walls. Second, structure line segments are recognized from the initial building facade structure based on the Regulated Block RANSAC (RB-RANSAC) algorithm. Third, geometric information such as distance, vector and positional relationship between structure line segments is considered to optimize the initial building facade structure. The proposed method can effectively extract and fit segment structures by considering the semantic and geometric information, obtaining significantly accurate and concise building facade structures. Case studies on 3D LPCD of local buildings and open-source datasets (Semantic3D) prove the extraction accuracy and efficiency of the proposed method.

Indoor Space Modeling and Parametric Component Construction Based on 3D Laser Point Cloud Data

In order to enhance modeling efficiency and accuracy, we utilized 3D laser point cloud data for indoor space modeling. Point cloud data was obtained with a 3D laser scanner and optimized with Autodesk Recap and Revit software to extract geometric information about the indoor environment. Furthermore, we proposed a method for constructing indoor elements based on parametric components. The research outcomes of this paper will offer new methods and tools for indoor space modeling and design. The approach of indoor space modeling based on 3D laser point cloud data and parametric component construction can enhance modeling efficiency and accuracy, providing architects, interior designers, and decorators with a better working platform and design reference.

Application of Airborne RadarTechnology in DEM Production

Since its appearance, airborne laser scanning technology has become more convenient and modern with the continuous progress and development of science and technology. Airborne LiDAR has a very wide range of applications in various fields. It can obtain the three-dimensional coordinates of the measured object comprehensively and with high quality. It has the advantages of high efficiency and high precision in DEM production. In this paper, DEM is produced in an area near Guantao County, Handan City. Firstly, airborne LiDAR is used to collect 3D laser point cloud data, and then software is used to process the point cloud. TerraSolid software is used to perform coordinate conversion and point cloud classification on the point cloud, and finally DEM is produced on the classified ground points. The result is a realistic and intuitive 3D model. The results show that the 3D point cloud data collected by airborne LiDAR can fully and accurately reflect the topographic and geomorphic information, and the software tools and algorithms in the processing process can effectively improve the availability and accuracy of the data, and the generated DEM data can provide important data support for terrain analysis, urban planning, natural resource management and other fields.

Accurate Extraction of Cableways Based on the LS-PCA Combination Analysis Method

In order to maintain a ski resort efficiently, regular inspections of the cableways are essential. However, there are some difficulties in discovering and observing the cable car cableways in the ski resort. This paper proposes a high-precision segmentation and extraction method based on the 3D laser point cloud data collected by airborne lidar to address these problems. In this method, first, an elevation filtering algorithm is used to remove ground points and low-height vegetation, followed by preliminary segmentation of the cableway using the spatial distribution characteristics of the point cloud. The ropeway segmentation and extraction are then completed using the least squares-principal component combination analysis method for parameter fitting. Additionally, we selected three samples of data from the National Alpine Ski Center to be used as test objects. The real value is determined by the number of point clouds manually deducted by CloudCompare. The extraction accuracy is defined as the ratio of the number of point clouds extracted by the algorithm to the number of point clouds manually extracted. While the environmental complexities of the samples differ, the algorithm proposed in this paper is capable of segmenting and extracting cableways with great accuracy, achieving a comprehensive and effective extraction accuracy rate of 90.59%, which is sufficient to meet the project’s requirements.

A Novel Method for Density Analysis of Repaired Point Cloud with Holes Based on Image Data

Repairing point cloud holes has become an important problem in the research of 3D laser point cloud data, which ensures the integrity and improves the precision of point cloud data. However, for the point cloud data with non-characteristic holes, the boundary data of point cloud holes cannot be used for repairing. Therefore, this paper introduces photogrammetry technology and analyzes the density of the image point cloud data with the highest precision. The 3D laser point cloud data are first formed into hole data with sharp features. The image data are calculated into six density image point cloud data. Next, the barycenterization Bursa model is used to fine-register the two types of data and to delete the overlapping regions. Then, the cross-section is used to evaluate the precision of the combined point cloud data to get the optimal density. A three-dimensional model is constructed for this data and the original point cloud data, respectively and the surface area method and the deviation method are used to compare them. The experimental results show that the ratio of the areas is less than 0.5%, and the maximum standard deviation is 0.0036 m and the minimum is 0.0015 m.

Fragmentation calculation method for blast muck piles in open-pit copper mines based on three-dimensional laser point cloud data

The current calculation methods for the blast fragmentation of muck piles (BFMP) do not consider three-dimensional (3D) feature information, such as concavity and convexity. Thus, their calculation results are inaccurate. In this work, 3D laser scanning technology with high precision, high efficiency, and real-time digitization is used to calculate fragmentation of blast muck piles in open-pit copper mines. The voxel cloud connectivity segmentation (VCCS) algorithm and locally convex connected patches (LCCP) algorithm are used to calculate BFMP from 3D laser point cloud data (3D LPCD). Meanwhile, an improved VCCS algorithm based on discrete features is proposed to solve the segmentation problem of 3D LPCD of small blast muck piles, which cannot be effectively segmented and thus greatly influence the 3D LPCD of large blast muck piles. An improved LCCP algorithm based on plane fitting solves the incorrect segmentation of the surface of large fragments into small pieces of fragments. Dexing Copper Mine, the largest open-pit copper mine in China, is taken as the research object. Results show that the accuracy of the calculation results is about 80% when the fragment sizes are 0.1–0.5 m. Moreover, almost all BFMP can be correctly calculated when the fragment size exceeds 0.5 m.

A Comparative Study for Indoor Planar Surface Segmentation via 3D Laser Point Cloud Data

In recent years, point cloud data generated with RGB-D cameras, 3D lasers, and 3D LiDARs have been employed frequently in robotic applications. In indoor environments, RGB-D cameras, which have short-range and can only describe the vicinity of the robots, generally are opted due to their low cost. On the other hand, 3D lasers and LiDARs can capture long-range measurements and generally are used in outdoor applications. In this study, we deal with the segmentation of indoor planar surfaces such as wall, floor, and ceiling via point cloud data. The segmentation methods, which are situated in Point Cloud Library (PCL) were executed with 3D laser point cloud data. The experiments were conducted to evaluate the performance of these methods with the publicly available Fukuoka indoor laser dataset, which has point clouds with different noise levels. The test results were compared in terms of segmentation accuracy and the time elapsed for segmentation. Besides, the general characteristics of each method were discussed. In this way, we revealed the positive and negative aspects of these methods for researchers that plan to apply them to 3D laser point cloud data.

New Approach in Integrated Basin Modelling: Melen Airborne LIDAR

Airborne LIDAR technology which has an increasing importance in recent years, has entered into the field of application of many disciplines by obtaining fast and highly accurate 3D data. It provides precise topography information with dense point cloud data as well as all details on the surface. Thus, it has become useful in all disciplines associated with space such as cartography, construction, city planning, forest, energy, hydrology, geology, transportation, telecommunications, security, disaster, aviation, and infrastructure. By mounting LIDAR measurement units on aircraft large areas can be measured relatively quickly and cost-effectively. In this study, Riegl Q680i scanner and CCNS5 flight management system were mounted to the aircraft. The digital elevation models; DEM (Digital Elevation Model) and DSM (Digital Surface Model) of the Melen basin, which is located within the boundaries of Düzce and Sakarya was generated using LIDAR point cloud data (.las format) with a point density of 16 points/m2 and also 1/1000 base maps of the basin were produced. In addition, many details such as road, slope, culvert, electricity poles were drawn in accordance with the principles of large-scale map construction regulations and transferred to GIS environment. The Melen basin with an important water storage area, boundaries, basin model, water collection lines, determination of flow directions and connections, the topographic surface of the basin sub-areas, morphology were created using 3D laser point cloud data. So, the digital terrain model of the basin in GIS environment is visualized with linear maps. LIDAR data provides 3D geometric and morphological information that cannot be obtained according to classical methods in this kind of engineering studies. Results suggest that the higher spatial resolution LIDAR-derived data are preferable and can introduce more detailed information about basin hydro geomorphic behaviours.

Research on the Construction of BIM Visualization Model Based on 3D Laser Point Cloud Data

The point cloud data of the main structure obtained by three-dimensional laser scanning technology is used as the basic data of the 3D modeling, and the point cloud data are processed by point cloud splicing, point cloud registration and point cloud de-noising. Taking the China-German energy saving demonstration center of Shenyang Jianzhu University as the research object, the "family" model of the building is established in the BIM modeling software Revit by the size of the point cloud data size, and then the BIM 3D model of the building is established so as to record and manage the building information on the building components. The experimental results show that the point cloud data obtained by 3D laser scanning has realized precise modeling and precise modeling in the process of building 3D model of building. Based on the idea of BIM, a three-dimensional model is established through the point cloud data. The model has accurate coordinate data, which provides the basis for the combination of BIM and GIS.

Potential of 3d laser point cloud data usage for the tourism industry.

Potential of 3d laser point cloud data usage for the tourism industry.

Potential of 3d laser point cloud data usage for the tourism industry

AbstractLaser scanning technology, both mobile and terrestrial, has encountered great technological advance during past few years. It gives us the opportunity to acquire great amounts of precisely measured data. 3d laser scanner technology is used in the development of tourism industry in some tourist places in Egypt, where this technology plays major roles in various fields that contribute to the industry of tourism, archaeology and preservation of ancient heritage. The point cloud plays major roles various fields that contribute to the tourism industry such as archeological exploration, heritage, monument preservation and 3d information technology. A much more suitable acquisition platform is 3d laser scanner where point cloud is collected with very high accuracy and details. The level of details is an essential requirement for tourism applications. National Research Institute of Astronomy and Geophysics NRIAG added Vehicle mobile laser scanner and terrestrial laser scanner systems to its Crustal Movements Laboratory–Geodynamic Department to investigate the potential of 3d laser scanners in various fields and disciplines such as the tourism industry and archaeological preservation. The main objective of this work is to cover several basic points, the elevation of the archaeological areas with high accuracy. Make photographic videos of archaeological sites. 3d modeling (virtual reality) is used for archaeological buildings and cemeteries and digitizing them with a very high accuracy especially as they are based on real data that helps in documenting them for future generations and preserving their historical value and restoration.

The Surface Flattening based on Mechanics Revision of the Tunnel 3D Point Cloud Data from Laser Scanner

The effective detection and supervision on tunnel deterioration are the important measures to ensure railway transportation operation security. The method of utilizing the mobile laser scanner to obtain space data with high resolution has been applied to get tunnel information. This paper provides a surface flattening algorithm based on mechanics revision which could be used to the 3D point cloud data from laser scanners. Utilizing this algorithm, the damage or deterioration located on the tunnel’s inner wall could be detected and located based on the 3D laser point cloud data. The first step of this algorithm is the reconstruction of triangular mesh surface to the point cloud data. Then, the surface flattening based on geometrical method is conducted to form a 2D plane. Energy optimization based on mechanics revision is utilized at the last step. The results of experiments in laboratory environments and practical metro tunnels evaluate the feasibility and the effectiveness of this algorithm.