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.

Research on BIM Model Reshaping Method Based on 3D Point Cloud Recognition

In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.

A Novel Airborne 3D Laser Point Cloud Hole Repair Algorithm Considering Topographic Features

Hole repair processing is an important part of point cloud data processing in airborne 3-dimensional(3D)laser scanning technology.Due to the fragmentation and irregularity of the surface morphology,when applying the 3D laser scanning technology to mountain mapping,the conventional mathematical cloud-based point cloud hole repair method is not ideal in practical applications.In order to solve this problem,we propose to repair the valley and ridge line first,and then repair the point cloud hole.The main technical steps of the method include the following points:First,the valley and ridge feature lines are extracted by the GIS slope analysis method;Then,the valley and ridge line missing from the hole are repaired by the mathematical interpolation method,and the repaired results are edited and inserted to the original point cloud;Finally,the traditional repair method is used to repair the point cloud hole whose valley line and ridge line have been repaired.Three experiments were designed and implemented in the east bank of the Xiaobaini River to test the performance of the proposed method.The results showed that compared with the direct point cloud hole repair method in Geomagic Studio software,the average repair accuracy of the proposed method,in the 16 m buffer zone of valley line and ridge line,is increased from 56.31 cm to 31.49 cm.The repair performance is significantly improved.

A voxel-based fine-scale 3D landscape pattern analysis using laser scanner point clouds

The landscape pattern metrics can quantitatively describe the characteristics of landscape pattern and are widely used in various fields of landscape ecology.Due to the lack of vertical information,2D landscape metrics cannot delineate the vertical characteristics of landscape pattern.Based on the point clouds,a high-resolution voxel model and several voxel-based 3D landscape metrics were constructed in this study and 3D metrics calculation results were compared with that of 2D metrics.The results showed that certain quantifying difference exists between 2D and 3D landscape metrics.For landscapes with different components and spatial configurations,significant difference was disclosed between 2D and 3D landscape metrics.3D metrics can better reflect the real spatial structure characteristics of the landscape than 2D metrics.

3DPhenoFish:Application for two-and three-dimensional fish morphological phenotype extraction from point cloud analysis

Fish morphological phenotypes are important resources in artificial breeding,functional gene mapping,and population-based studies in aquaculture and ecology.Traditional morphological measurement of phenotypes is rather expensive in terms of time and labor.More importantly,manual measurement is highly dependent on operational experience,which can lead to subjective phenotyping results.Here,we developed 3DPhenoFish software to extract fish morphological phenotypes from three-dimensional(3D)point cloud data.Algorithms for background elimination,coordinate normalization,image segmentation,key point recognition,and phenotype extraction were developed and integrated into an intuitive user interface.Furthermore,18 key points and traditional 2D morphological traits,along with 3D phenotypes,including area and volume,can be automatically obtained in a visualized manner.Intuitive fine-tuning of key points and customized definitions of phenotypes are also allowed in the software.Using 3DPhenoFish,we performed high-throughput phenotyping for four endemic Schizothoracinae species,including Schizopygopsis younghusbandi,Oxygymnocypris stewartii,Ptychobarbus dipogon,and Schizothorax oconnori.Results indicated that the morphological phenotypes from 3DPhenoFish exhibited high linear correlation(>0.94)with manual measurements and offered informative traits to discriminate samples of different species and even for different populations of the same species.In summary,we developed an efficient,accurate,and customizable tool,3DPhenoFish,to extract morphological phenotypes from point cloud data,which should help overcome traditional challenges in manual measurements.3DPhenoFish can be used for research on morphological phenotypes in fish,including functional gene mapping,artificial selection,and conservation studies.3DPhenoFish is an open-source software and can be downloaded for free at https://github.com/lyh24k/3DPhenoFish/tree/master.

Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors

To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings.

Building 3D CityGML models of mining industrial structures using integrated UAV and TLS point clouds

Mining industrial areas with anthropogenic engineering structures are one of the most distinctive features of the real world.3D models of the real world have been increasingly popular with numerous applications,such as digital twins and smart factory management.In this study,3D models of mining engineering structures were built based on the CityGML standard.For collecting spatial data,the two most popular geospatial technologies,namely UAV-SfM and TLS were employed.The accuracy of the UAV survey was at the centimeter level,and it satisfied the absolute positional accuracy requirement of creat-ing all levels of detail(LoD)according to the CityGML standard.Therefore,the UAV-SfM point cloud dataset was used to build LoD 2 models.In addition,the comparison between the UAV-SfM and TLS sub-clouds of facades and roofs indicates that the UAV-SfM and TLS point clouds of these objects are highly consistent,therefore,point clouds with a higher level of detail and accuracy provided by the integration of UAV-SfM and TLS were used to build LoD 3 models.The resulting 3D CityGML models include 39 buildings at LoD 2,and two mine shafts with hoistrooms,headframes,and sheave wheels at LoD3.

Usage of 3D Point Cloud Data in BIM （Building Information Modelling）： Current Applications and Challenges

BIM （building information modelling） has gained wider acceptance in the A/E/C （architecture/engineering/construction） industry in the US and internationally. This paper presents current industry approaches of implementing 3D point cloud data in BIM and VDC （virtual design and construction） applications during various stages of a project life cycle and the challenges associated with processing the huge amount of 3D point cloud data. Conversion from discrete 3D point cloud raster data to geometric/vector BIM data remains to be a labor-intensive process. The needs for intelligent geometric feature detection/reconstruction algorithms for automated point cloud processing and issues related to data management are discussed. This paper also presents an innovative approach for integrating 3D point cloud data with BIM to efficiently augment built environment design, construction and management.

Numerical Investigation of Laser Surface Hardening of AISI 4340 Using 3D FEM Model for Thermal Analysis of Different Laser Scanning Patterns

Laser surface hardening is becoming one of the most successful heat treatment processes for improving wear and fatigue properties of steel parts. In this process, the heating system parameters and the material properties have important effects on the achieved hardened surface characteristics. The control of these variables using predictive modeling strategies leads to the desired surface properties without following the fastidious trial and error method. However, when the dimensions of the surface to be treated are larger than the cross section of the laser beam, various laser scanning patterns can be used. Due to their effects on the hardened surface properties, the attributes of the selected scanning patterns become significant variables in the process. This paper presents numerical and experimental investigations of four scanning patterns for laser surface hardening of AISI 4340 steel. The investigations are based on exhaustive modelling and simulation efforts carried out using a 3D finite element thermal analysis and structured experimental study according to Taguchi method. The temperature distribution and the hardness profile attributes are used to evaluate the effects of heating parameters and patterns design parameters on the hardened surface characteristics. This is very useful for integrating the scanning patterns’ features in an efficient predictive modeling approach. A structured experimental design combined to improved statistical analysis tools is used to assess the 3D model performance. The experiments are performed on a 3 kW Nd:Yag laser system. The modeling results exhibit a great agreement between the predicted and measured values for the hardened surface characteristics. The model evaluation reveals also its ability to provide not only accurate and robust predictions of the temperature distribution and the hardness profile as well an in-depth analysis of the effects of the process parameters.

Research on 3D Laser Scanning Reconstruction of Ancient Buildings Combined with BIM Technology

After more than 30 years of scientific and social development, surveying and mapping technology by leaps and bounds, engineering surveying technology has undergone tremendous changes. In the process of protecting ancient buildings, it is necessary to obtain the precise dimensions of architectural details. In this study, the path of 3D laser scanning combined with BIM technology is explored. Taking the observation and protection of the ancestral hall of the Liu family as an example, this study aims to draw drawings that reflect the relevant information about the ancient buildings, the accurate three-dimensional model of ancient buildings is established with BIM technology, which provides new methods and ideas for the research and protection of ancient buildings. .

Reconstructing DEM using TLS point cloud data and NURBS surface

Underground coal mining inevitably results in land surface subsidence.Acquiring information on land surface subsidence is important in the detection of surface change.However,conventional data acquisition techniques cannot always retrieve information on whole subsidence area.This study focuses on the reconstruction of a digital elevation model（DEM） with terrestrial laser scanning（TLS） point cloud data.Firstly,the methodology of the DEM with terrestrial 3-dimensional laser scanning is introduced.Then,a DEM modeling approach that involves the application of curved non-uniform rational B-splines（NURBS） surface is put forward.Finally,the performance of the DEM modeling approach with different surface inverse methods is demonstrated.The results indicate that the DEM based on the point cloud data and curved NURBS surface can achieve satisfactory accuracy.In addition,the performance of the hyperbolic paraboloid appears to be better than that of the elliptic paraboloid.The reconstructed DEM is continuous and can easily be integrated into other programs.Such features are of great importance in monitoring dynamic ground surface subsidence.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

A review of road 3D modeling based on light detection and ranging point clouds

Increasing development of accurate and efficient road three-dimensional(3D)modeling presents great opportunities to improve the data exchange and integration of building information modeling(BIM)models.3D modeling of road scenes is crucial for reference in asset management,construction,and maintenance.Light detection and ranging(Li DAR)technology is increasingly employed to generate high-quality point clouds for road inventory.In this paper,we specifically investigate the use of Li DAR data for road 3D modeling.The purpose of this review is to provide references about the existing work on the road 3D modeling based on Li DAR point clouds,critically discuss them,and provide challenges for further study.Besides,we introduce modeling standards for roads and discuss the components,types,and distinctions of various Li DAR measurement systems.Then,we review state-of-the-art methods and provide a detailed examination of road segmentation and feature extraction.Furthermore,we systematically introduce point cloud-based 3D modeling methods,namely,parametric modeling and surface reconstruction.Parameters and rules are used to define model components based on geometric and non-geometric information,whereas surface modeling is conducted through individual faces within its geometry.Finally,we discuss and summarize future research directions in this field.This review can assist researchers in enhancing existing approaches and developing new techniques for road modeling based on Li DAR point clouds.

Application of Three-Dimensional Laser Scanning and Surveying in Geological Investigation of High Rock Slope

The appearance of 3D laser scanning technology is one of the most important technology revolutions in surveying and mapping field. It can be widely used in many interrelated fields, such as engineering constructions and 3D measurements, owing to its prominent characteristics of the high efficiency and high precision. At present its application is still in the initial state, and it is quite rarely used in China, especially in geotechnical engineering and geological engineering fields. Starting with a general introduction of 3D laser scanning technology, this article studies how to apply the technology to high rock slope investigations. By way of a case study, principles and methods of quick slope documentation and occurrence measurement of discontinuities are discussed and analyzed. Analysis results show that the application of 3D laser scanning technology to geotechnical and geological engineering has a great prospect and value.

Radiotherapy-customized head immobilization masks:from modeling and analysis to 3D printing

Immobilization devices may be a valuable aid to ensure the improved effectiveness of radiotherapy treatments where constraining the movements of specific anatomical segments is crucial. This need is also present in other situations, specifically when the superposition of various medical images is required for fine identification and characterization of some pathologies. Because of their structural characteristics, existing head immobilization systems may be claustrophobic and very uncomfortable for patients, during both the modeling and usage stages. Because of this, it is important to minimize all the discomforts related to the mask to alleviate patients’ distress and to simultaneously guarantee and maximize the restraint effectiveness of the mask. In the present work, various head immobilization mask models are proposed based on geometrical information extracted from computerized tomography images and from 3D laser scanning point clouds. These models also consider the corresponding connection to a radiotherapy table, as this connection is easily altered to accommodate various manufacturers’ solutions. A set of materials used in the radiotherapy field is considered to allow the assessment of the stiffness and strength of the masks when submitted to typical loadings.

Aggregate Point Cloud Geometric Features for Processing

As 3D acquisition technology develops and 3D sensors become increasingly affordable,large quantities of 3D point cloud data are emerging.How to effectively learn and extract the geometric features from these point clouds has become an urgent problem to be solved.The point cloud geometric information is hidden in disordered,unstructured points,making point cloud analysis a very challenging problem.To address this problem,we propose a novel network framework,called Tree Graph Network(TGNet),which can sample,group,and aggregate local geometric features.Specifically,we construct a Tree Graph by explicit rules,which consists of curves extending in all directions in point cloud feature space,and then aggregate the features of the graph through a cross-attention mechanism.In this way,we incorporate more point cloud geometric structure information into the representation of local geometric features,which makes our network perform better.Our model performs well on several basic point clouds processing tasks such as classification,segmentation,and normal estimation,demonstrating the effectiveness and superiority of our network.Furthermore,we provide ablation experiments and visualizations to better understand our network.

Development of 3D Scanning System for Robotic Plasma Processing of Medical Products with Complex Geometries

This paper describes the development of an intelligent automated control system of a robot manipulator for plasma treatment of medical implants with complex shapes.The two-layer coatings from the Ti wire and hydroxyapatite powders are applied on the surface of Ti medical implants by microplasma spraying to increase the biocompatibility of implants.The coating process requires precise control of a number of parameters,particularly the plasma spray distance and plasma jet traverse velocity.Thus,the development of the robotic plasma surface treatment involves automated path planning.The key idea of the proposed intelligent automatic control system is the use of data of preliminary three-dimensional (3D) scanning of the processed implant by the robot manipulator.The segmentation algorithm of the point cloud from laser scanning of the surface is developed.This methodology is suitable for robotic 3D scanning systems with both non-contact laser distance sensors and video cameras,used in additive manufacturing and medicine.

3D Object Detection with Attention:Shell-Based Modeling

LIDAR point cloud-based 3D object detection aims to sense the surrounding environment by anchoring objects with the Bounding Box(BBox).However,under the three-dimensional space of autonomous driving scenes,the previous object detection methods,due to the pre-processing of the original LIDAR point cloud into voxels or pillars,lose the coordinate information of the original point cloud,slow detection speed,and gain inaccurate bounding box positioning.To address the issues above,this study proposes a new two-stage network structure to extract point cloud features directly by PointNet++,which effectively preserves the original point cloud coordinate information.To improve the detection accuracy,a shell-based modeling method is proposed.It roughly determines which spherical shell the coordinates belong to.Then,the results are refined to ground truth,thereby narrowing the localization range and improving the detection accuracy.To improve the recall of 3D object detection with bounding boxes,this paper designs a self-attention module for 3D object detection with a skip connection structure.Some of these features are highlighted by weighting them on the feature dimensions.After training,it makes the feature weights that are favorable for object detection get larger.Thus,the extracted features are more adapted to the object detection task.Extensive comparison experiments and ablation experiments conducted on the KITTI dataset verify the effectiveness of our proposed method in improving recall and precision.

Intelligent virtualization of crane lifting using laser scanning technology

Background This paper presents an intelligent path planner for lifting tasks by tower cranes in highly complex environments,such as old industrial plants that were built many decades ago and sites used as tentative storage spaces.Generally,these environments do not have workable digital models and 3 D representations are impractical.Methods The current investigation introduces the use of cutting edge laser scanning technology to convert real environments into virtualized versions of the construction sites or plants in the form of point clouds.The challenge is in dealing with the large point cloud datasets from the multiple scans needed to produce a complete virtualized model.The tower crane is also virtualized for the purpose of path planning.A parallelized genetic algorithm is employed to achieve intelligent path planning for the lifting task performed by tower cranes in complicated environments taking advantage of graphics processing unit technology,which has high computing performance yet low cost.Results Optimal lifting paths are generate d in several seconds.

三维激光扫描技术结合3DS MAX在建筑物逆向建模中的应用

针对目前建筑物逆向建模中存在的数据采集效率低、模型精度低、模型效果不真实等问题,提出了一种三维激光扫描技术结合3DS MAX对建筑物进行逆向建模的方法。使用架站式三维激光扫描仪对目标建筑物进行多站扫描,利用SCENE软件对多站点云数据进行配准、去噪生成三维点云,基于三维点云生成建筑物各立面的正射影像,将影像导入AutoCAD并绘制建筑物二维平立面矢量图,将各平立面矢量图导入3DS MAX软件,经建立白模、纹理贴图等过程,生成目标建筑三维模型,最后对模型的精度进行了验证。结果表明,该方法可以高效地建立高精度且具有逼真效果的建筑物三维模型。