ADAPTIVE MESHING AND DETAIL-REDUCTION OF 3D-POINT CLOUDS FROM LASER SCANS (original) (raw)
2000
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Abstract
D laser scanners become more and more popular especially for measuring construction sites, in the field of architecture and for preservation of monuments. As these scanners can only record discrete data sets (point clouds), it is necessary to mesh these sets for getting closed 3D models and take advantage of 3D graphics acceleration of modern graphics hardware. The meshing process
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Hybrid technique for three-dimensional modeling from laser scanner's point clouds
Final Master Thesis, 2013
The use of laser scanner to model an object in three dimensions is important in engineering application. Laser scanner generates point clouds that resemble the topology surface of object. Three-dimensional model (3D) of scanned object can be generated from the point clouds. The Hybrid technique that combines the modified Iterative Closet Point (ICP) algorithm and surface reconstruction algorithm that are used to generate 3D model from point clouds is developed. Hybrid technique is divided into local and global methods. Local method is the modification of ICP and surface reconstruction algorithm. Global method uses the local method to generate 3D model from point clouds. The K Nearest Neighbour (KNN) method is used to define corresponding point between two point clouds in ICP algorithm. Tolerance distance is used to control the number of corresponding points, and ICP iteration will terminate when the number of corresponding points for the current iteration is less than the number of corresponding points for previous iteration. In order to reduce the effect of noise in surface, the point cloud is represented as Adaptive Moving Least Square Surface (AMLS). 3D surface of AMLS is reconstructed by using Big Delaunay ball. Hybrid technique has been applied into point clouds scanned by using Vivid910, NextEngine and Faro laser scanners. The minimum and maximum range average deviation value between the 3D model from Hybrid technique and commercial software, RapidForm is small (around 0.005mm to 0.554mm). Difference of measurement value between real objects and the 3D model is around -0.030cm to 0.200cm. Hybrid technique in this research has successfully generated the 3D model from point clouds and can be used to develop the new software system for 3D applications.
3D OBJECT MODEL RECONSTRUCTION BASED ON LASER SCANNING POINT CLOUD DATA
Three dimensional (3D) reconstruction has been widely applied in urban planning, digital city, and the conservation of cultural/archaeological heritage etc. to re-build 3D object geometry. In the situation where the objects are irregular and have complex-structure, the use of conventional methods is time-consuming and mostly not practicable because of the workload involved and the detail of roofs or footprints cannot be modelled and low accuracy. The paper introduces the method of reconstructing 3D object model based on point clouds acquired by 3D terrestrial laser scanner including data acquisition, data processing, multiple scan registration, 3D modelling and texture mapping. The experiment result shows that, the method can effectively and quickly reconstruct 3D object geometry with many details, especially in 3D city model and cultural/archaeological heritage."
2012
Terrestrial laser scanners deliver a dense point-wise sampling of an object’s surface. For many applications a surface-like reconstruction is required. The most typical example is the visualization of the scanned data. Traditional approaches use meshing algorithms to reconstruct and triangulate the surface represented by the points. Especially in cultural heritage, where complex objects with delicate structures are recorded in highly detailed scans, this process is not without problems. Often long and tedious manual clean-up procedures are required to achieve satisfactory results. After summarizing our experience with current meshing technology we therefore explore alternative approaches for surface reconstruction. An alternative approach presented within this paper is point splatting. We have developed an algorithm to compute a suitable surfel representation directly from the raw laser scanner data. This results in a speedy and fully automated procedure for surface reconstruction. ...
CAD-Based Modeling Using Three Dimensional Point Cloud Data
2021
Preserving historical and cultural artifacts through generations is essential for maintaining the roots and ensuring the development of any civilization. Conservation and restoration works are crucial in order to save numerous historical and cultural heritages in our country and the world and also pass on them from generation to generation. Nowadays, the increasing development in measurement technologies and the integration of photogrammetry into architectural applications have provided different perspective in architectural documentation applications. In this context, Terrestrial laser scanning method is a current method used in documentation studies today. The most important advantages of terrestrial laser scanning in this study are as follows: -the point cloud data obtained by terrestrial laser scanners provides the opportunity to reach the correct data at the desired frequency in a short time, -obtaining appropriate and practical results for the targeted study,-the possibility of using scanners in different working areas. In this context, laser scanners have become one of the popular methods in which effective and successful results are obtained in architectural documentation projects such as survey, restitution and restoration. Within the scope of this study, ''Ali Efendi Muallimhanesi'', which is one of the historical and cultural heritage of Konya province, was scanned with a terrestrial laser scanner and 3D drawing and modeling was carried out with the help of the cad-based modeling tools only using 3D point cloud data.
Online Triangulation of Laser-Scan Data
Proceedings of the 17th International Meshing Roundtable
Fig. 1. A piggy bank. Original object (left), wire-frame (center), and smooth shaded triangulation with uncertainty visualization (right). Summary. Hand-held laser scanners are used massively in industry for reverse engineering and quality measurements. In this process, it is difficult for the human operator to scan the target object completely and uniformly. Therefore, an interactive triangulation of the scanned points can assist the operator in this task. Our method computes a triangulation of the point stream generated by the laser scanner online, i.e., the data points are added to the triangulation as they are received from the scanner. Multiple scanned areas and areas with a higher point density result in a finer mesh and a higher accuracy. On the other hand, the vertex density adapts to the estimated surface curvature. To assist the human operator the resulting triangulation is rendered with a visualization of its faithfulness. Additionally, our triangulation method allows for a level-of-detail representation to reduce the mesh complexity for fast rendering on low-cost graphics hardware.
3D Data Acquisition for Indoor Assets Using Terrestrial Laser Scanning
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013
The newly development of technology clearly shows an improvement of three-dimension (3D) data acquisition techniques. The requirements of 3D information and features have been obviously increased during past few years in many related fields. Generally, 3D visualization can provide more understanding and better analysis for making decision. The need of 3D GIS also pushed by the highly demand of 3D in geospatial related applications as well as the existing fast and accurate 3D data collection techniques. This paper focuses on the 3D data acquisition by using terrestrial laser scanning. In this study, Leica C10 terrestrial laser scanner was used to collect 3D data of the assets inside a computer laboratory. The laser scanner device is able to capture 3D point cloud data with high speed and high accuracy. A series of point clouds was produced from the laser scanner. However, more attention must be paid during the point clouds data processing, 3D modelling, and analysis of the laser scanned data. Hence, this paper will discuss about the data processing from 3D point clouds to 3D models. The processing of point cloud data divided into pre-processing (data registration and noise filter) and post-processing (3D modelling). During the process, Leica Cyclone 7.3 was used to process the point clouds and SketchUp was used to construct the 3D asset models. Afterward, the 3D asset models were exported to multipatch geometry format, which is a 3D GIS-ready format for displaying and storing 3D model in GIS environment. The final result of this study is a set of 3D asset models display in GIS-ready format since GIS can provides the best visual interpretation, planning and decision making process. This paper shows the 3D GIS data could be produced by laser scanning technology after further processing of point cloud data.
Point Clouds Construction Algorithm From a Home-made Laser Scanner
Reverse Engineering (RE) technique is now becoming an emerging technology for modeling a physical part into a digital model. This is eventually required when one has to redesign an old product or to remanufacture a non-filed engineering product. This technique involves manufacturing a new interesting product or redesigning an existing product in order to quickly respond the consumer needs. This approach has an important role in facing the tight industrial competition. Producers are racing to implement this new technology to win the market. Hardware to carry out reverse engineering is still an expensive thing. In implementing this technique in an educational laboratory a self-made scanning facility is developed. The scanner plots a silhouette lines on an object surface and a camera is used to take the images of the object. These lines are then mathematically transformed to get a digital representation of the object surface. The digital information is constructed from a huge number of points that represent the surface points of the scanned object. Coordinates of those points are calculated using triangulation method. Image processing and manipulation are conducted in MATLAB to easily process the digital image and to show the 3-D representation.
Fast and accurate close range 3D modelling by laser scanning system
… REMOTE SENSING AND …, 2002
Completeness, speed, accuracy are some aspects of the laser scanning system for the acquisition of complex structures and sites. Complete geometry of exposed surface is remotely captured in minutes in the form of dense, accurate "3D point clouds", ready for immediate use. This technique is used for architecture, virtual reality, heritage preservation and some other engineering and civil applications. Laser scanning technology offers many advantages over traditional surveying and photogrammetric methods: better quality results, improved safety during data capture, no interference with construction and operations activities, no time consuming, simplicity and easiness in learning. Furthermore in many cases, it can provide significant cost saving in both capturing surface geometry and in generating CAD models or otherwise using the gathered data. We applied the laser scanner Callidus Precision System to digitise the shape of the three-dimensional small temple inside the Mole Vanvitelliana in Ancona to build a 3D model. It is a complicated task, made harder by the unusually large size of the data sets. We processed the data by several TIN methods to obtain CAD meshes and realize an efficient 3D rendered virtual object close to the reality.
METHODOLOGY TO CREATE 3D MODELS FOR AUGMENTED REALITY APPLICATIONS USING SCANNED POINT CLOUDS
2014
Precise digital documentation of cultural heritage assets is essential for its preservation and protection. This documentation increases the efficiency of scientific studies that are being carried out during the restoration and renovation process. Precise digital documentation makes use of different laser scanners technologies. 3D scanning devices usually provide a large amount of point clouds, which require long post-processing times and large storage space. This paper presents a methodology to obtain simplified 3D models designed to remove redundant points and maintain only representative points, preserving the 3D model aspect and allowing the 3D models to be implemented in different augmented reality application on mobile devices. The 3D mesh optimization methods that have been analyzed and compared are dedicated 3D mesh optimization software (CATIA and Geomagic Studio), open source tools such (Meshlab) and a numerical computing environment (MATLAB). The methodology proposes a split step that can be applied to both assemblies and reconstructed objects. In this step the 3D scan is divided into components (for assemblies) or original parts/restored parts (for restored cultural heritage assets). The efficiency and robustness are demonstrated using different 3D scanned Dacian ar-tifacts.
Design, Implementation and Comparison of Low-Cost Laser Scanning Systems for 3D Modeling
The 7th International Conference on Information Technology, 2015
3 dimensional (3D) modeling of an object or an environment using point clouds is an important problem in many scientific fields such as photogrammetry, remote sensing, materials processing, reverse engineering, construction industry, virtual reality and medicine etc. Laser scanning is an effective technique that facilitates 3D modeling process with providing large amount of 3D point cloud data in a short time. In this study, design process of point laser sensor and line laser sensor based low cost scanner systems is proposed. Performed 3D data measurements with these two different laser scanners show that; point laser range sensor based scanner, that can capture lesser 3D point for per second, provides more detailed and more sensitive measurements. It can be preferred in applications when the details are very important and are suitable for modeling small objects. However, line laser range sensor based scanner can capture much more 3D point data per second and it is suitable for applications where time critical models with large objects and environment.
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From point cloud to surface: modeling structures in laser scanner point clouds
Proceedings of the ISPRS …, 2007
The automatic modeling of precise structures from randomly distributed laser points derived from laser scanner data is a very hard problem, not completely solved and problematic in case of incomplete, noisy and sparse data. The generation of polygonal models that can satisfy high modeling and visualization demands is required in different applications, like architecture, archaeology, city planning, virtual reality applications and other graphics applications. The goal is always to find a way to create a computer model of an object which best fits the reality. Polygons are usually the ideal way to accurately represent the results of measurements, providing an optimal surface description. While the generation of digital terrain models has a long tradition and has found efficient solutions, the correct 3D modeling of closed surfaces or free-form objects is of recent nature, a not completely solved problem and still an important issue investigated in many research activities. In this paper we develop an approach for converting a laser scanner point cloud into a realistic 3D polygonal model that can satisfy high modeling and visualization demands. Close range photogrammetry deals since many years with manual or automatic image measurements. Now laser scanners are also becoming a standard source for input data in many application areas, providing millions of points. As a consequence, the problem of generating high quality polygonal models of objects from randomly distributed laser points is getting more and more attention. After reviewing some results in this context, we will describe a full approach for turning a usual unstructured point cloud into a consistent polygonal model. Finally, the polygonal model is turned into a hierarchical nodes network similar to VRML. A novel laserscanning processing tool, LSM3D (Laser Scanner Modeling 3D), has been developed and tested over different examples related with architectonic buildings.
FROM POINT SAMPLES TO SURFACES - ON MESHING AND ALTERNATIVES
Terrestrial laser scanners deliver a dense point-wise sampling of an object's surface. For many applications a surface-like reconstruction is required. The most typical example is the visualization of the scanned data. Traditional approaches use meshing algorithms to reconstruct and triangulate the surface represented by the points. Especially in cultural heritage, where complex objects with delicate structures are recorded in highly detailed scans, this process is not without problems. Often long and tedious manual clean-up procedures are required to achieve satisfactory results. After summarizing our experience with current meshing technology we therefore explore alternative approaches for surface reconstruction. An alternative approach presented within this paper is point splatting. We have developed an algorithm to compute a suitable surfel representation directly from the raw laser scanner data. This results in a speedy and fully automated procedure for surface reconstruction. The properties of the different approaches for surface reconstruction are discussed considering a practical example from the field of cultural heritage. The Panagia Kera in Kritsa near Agios Nikolaos on the island of Crete was chosen as a suitable example.
A system for reconstruction from point clouds in 3D: Simplification and mesh representation
2010 11th International Conference on Control Automation Robotics & Vision, 2010
In this paper we present a complete system for acquisition of fused (textured) point clouds in 3D, from a Laser Range Finder (LRF) and a CCD camera. Furthermore, we describe an approach to build and process the resulting models, including their pre-processing and mesh simplification. This approach allows manipulating the resulting data structure into consistent geometric representations, which can be further adapted based on user requirements. The advantage of our system is that of low computational cost, ease of use and accuracy in the representation of the environment, even without prior data smoothing.
Evaluation and correction of laser-scanned point clouds
Videometrics VIII, 2005
The digitalization of real-world objects is of great importance in various application domains. E. g.in industrial processes quality assurance is very important. Geometric properties of workpieces have to be measured. Traditionally, this is done with gauges which is somewhat subjective and time-consuming. We developed a robust optical laser scanner for the digitalization of arbitrary objects, primary, industrial workpieces. As measuring principle we use triangulation with structured lighting and a multi-axis locomotor system. Measurements on the generated data leads to incorrect results if the contained error is too high. Therefore, processes for geometric inspection under non-laboratory conditions are needed that are robust in permanent use and provide high accuracy as well as high operation speed. The many existing methods for polygonal mesh optimization produce very esthetic 3D models but often require user interaction and are limited in processing speed and/or accuracy. Furthermore, operations on optimized meshes consider the entire model and pay only little attention to individual measurements. However, many measurements contribute to parts or single scans with possibly strong differences between neighboring scans being lost during mesh construction. Also, most algorithms consider unsorted point clouds although the scanned data is structured through device properties and measuring principles. We use this underlying structure to achieve high processing speeds and extract intrinsic system parameters to use them for fast pre-processing.
Modeling and Visualization Objects from Point Cloud Data Surveyed With Terrestrial Laser Scanner
In this paper we present the problems of converting a measured point cloud surveyed with a terrestrial laser scanner into a realistic 3D polygonal model that can satisfy high modeling and visualization demands. Today 3D scanners are becoming a standard source for input data in many application areas, like architecture, archaeology and surveying. We convert a usually unstructured point cloud into a consistent polygonal model. We analyze the principal problems concerning the surface interpolation and the visualization modes of 3D objects. Finally we present the most popular software packages, languages and libraries used for visualization of point cloud data.
From point cloud to surface: the modeling and visualization problem
International Workshop on Visualization and Animation …, 2003
In this paper we address all the problems and solutions of converting a measured point cloud into a realistic 3D polygonal model that can satisfy high modeling and visualization demands. Close range photogrammetry deals since many years with manual or automatic image measurements. Now 3D scanners are also becoming a standard source for input data in many application areas, providing for millions of points. As a consequence, the problem of generating high quality polygonal meshes of objects from unorganized point clouds is receiving more and more attention. After reviewing the different 3D shape techniques for surface reconstruction, we will report the full process of converting a usually unstructured point cloud into a consistent polygonal model. Some triangulation algorithms, modeling methods and visualization techniques are also described and different examples are presented.
Processing and interactive editing of huge point clouds from 3D scanners
Computers & Graphics, 2008
This paper describes a new out-of-core multi-resolution data structure for real-time visualization, interactive editing and externally efficient processing of large point clouds. We describe an editing system that makes use of the novel data structure to provide interactive editing and preprocessing tools for large scanner data sets. Using the new data structure, we provide a complete tool chain for 3D scanner data processing, from data preprocessing and filtering to manual touch-up and real-time visualization. In particular, we describe an out-of-core outlier removal and bilateral geometry filtering algorithm, a toolset for interactive selection, painting, transformation, and filtering of huge out-of-core point-cloud data sets and a real-time rendering algorithm, which all use the same data structure as storage backend. The interactive tools work in real-time for small model modifications. For large scale editing operations, we employ a tworesolution approach where editing is planned in real-time and executed in an externally efficient offline computation afterwards. We evaluate our implementation on example data sets of sizes up to 63 GB, demonstrating that the proposed technique can be used effectively in real-world applications.
Optics and Lasers in Engineering, 2015
Terrestrial laser scanners are frequently used in most of measurement application, particularly in documentation and restoration studies of indoor historical structures, and in acquiring facade reliefs. When compared to a photogrammetric method, terrestrial laser scanners have the ability to give three dimensional point cloud data directly in a fast and detailed way. High data density of point cloud data is a challenging factor in texture-map operations during documentation and restoration of historical artifacts with more indoor spaces. When coordinate information for terrestrial laser scanner point cloud data is documented, it is seen that there is no regular order and classification for the data. The aim of this study is to suggest the mathematical filtering algorithm for segmentation work towards separation of planar surfaces which have different depths and parallel to each other and which can be frequently encountered in the indoor spaces from the data of terrestrial laser scanner. Filtering function for segmentation used, is based on the distance of a point to the plane. This algorithm has been chosen for the advantage of the rapid and easy results for extracting 3D coordinate data in texture mapping process. The MatLAB interface has been developed for using this method and analyzing the results for application which is detected how many different surfaces exist according to the statistical deviation amount. In the application, test data with 21932 points was segmented by separating it into 16 points in total with four different planes and four corner points per plane. Surfaces with four different depths were obtained as the result of the research. Each of them included four points. These segmented surfaces consisting of four points will facilitate integrated data production by integrating vectorial terrestrial laser scanner data into raster camera data, without the need to conventional measurements that accelerate particularly documentation and modeling in the fields of historical indoor areas.
2011 18th IEEE International Conference on Image Processing, 2011
We present an automatic approach for modeling buildings from aerial LiDAR data. The method produces accurate, watertight and compact meshes under planar constraints which are especially designed for urban scenes. The LiDAR point cloud is classified through a non-convex energy minimization problem in order to separate the points labeled as building. Roof structures are then extracted from this point subset, and used to control the meshing procedure. Experiments highlight the potential of our method in term of minimal rendering, accuracy and compactness.
RECOGNISING STRUCTURE IN LASER SCANNER POINT CLOUDS1
2004
Both airborne and terrestrial laser scanners are used to capture large point clouds of the objects under study. Although for some applications, direct measurements in the point clouds may already suffice, most applications require an automatic processing of the point clouds to extract information on the shape of the recorded objects. This processing often involves the recognition of specific geometric