ADAPTIVE MESHING AND DETAIL-REDUCTION OF 3D-POINT CLOUDS FROM LASER SCANS (original) (raw)
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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.
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. ...
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.