Study on Preprocessing Methods for Color 3D Point Cloud

2004 ◽  
Vol 471-472 ◽  
pp. 716-721
Author(s):  
X.D. Zhang ◽  
Chang Ku Sun ◽  
C. Wang ◽  
S.H. Ye
Keyword(s):  
Automatic System ◽  
Point Cloud ◽  
Laser Scanning ◽  
Reduction Method ◽  
Three Dimension ◽  
3D Point Cloud ◽  
Model Reconstruction ◽  
Selection Methods ◽  
Noise Data ◽  
Data Reduction Method

This paper provides a preprocessing flow for color three-dimension (3D) point cloud according to the characteristics of laser scanning data. The preprocessing methods and their functions are introduced in detail. Automatic system decision and manual polygon selection methods are applied to eliminate unwanted and noise data successfully, which possibly make improper color models reconstructed. A data reduction method is presented based on Grid reduction method considering color-boundary preservation. It can effectively avoid shape and color distortion in model reconstruction. Several experimental results are presented to indicate the feasibility and reliability of these methods, which can be broadly applied in various fields of products design, antiques and art wares digitization, etc.

scholarly journals Point-Cloud Models of Historical Barns – Spatial Discrepancies of Laser Scanning versus Robotic Total Station

10.29007/2493 ◽  
2020 ◽  
Author(s):  
Gustavo Maldonado ◽  
Marcel Maghiar ◽  
Brent Tharp ◽  
Dhruv Patel
Keyword(s):  
Service Learning ◽  
Point Cloud ◽  
Laser Scanning ◽  
3D Point Cloud ◽  
Spatial Accuracy ◽  
Total Station ◽  
Cloud Models ◽  
Bulloch County ◽  
Southern University ◽  
Robotic Total Station

This study considers the generation of virtual, 3D point-cloud models of seven deteriorating historical, agricultural barns in Bulloch County, Georgia, USA, for preservation purposes. The work was completed as a service-learning project in a course on Terrestrial Light Detection and Ranging (T-LiDAR), offered at Georgia Southern University. The resulting models and fly-through videos were donated to Bulloch County Historical Society and to the Georgia Southern Museum, to make them available to the general public and future generations. Additionally, one of the seven barns was selected to be extensively measured to estimate the relative spatial accuracy of all seven resulting 3D point-cloud models, with respect to measurements completed with a highly accurate instrument. Three accurate benchmarks were established around it for georeferencing purposes. The positions of 44 points were measured in the field via an accurate, one- second, robotic total-station (RTS) instrument. Also, the coordinates of the same points were acquired from within georeferenced and non-georeferenced point-cloud models. These points defined 259 distances. They were compared to determine their discrepancy statistics. It was observed that this process produced virtual models with an approximate maximum spatial discrepancy of one-half inch (0.5 in) with respect to measurements performed by a highly accurate RTS device. There were no substantial differences in the relative accuracies of the georeferenced and non-georeferenced models.

scholarly journals A FAST METHOD FOR MEASURING THE SIMILARITY BETWEEN 3D MODEL AND 3D POINT CLOUD

2016 ◽  
Vol XLI-B1 ◽  
pp. 725-728
Author(s):  
Zongliang Zhang ◽  
Jonathan Li ◽  
Xin Li ◽  
Yangbin Lin ◽  
Shanxin Zhang ◽  
...  
Keyword(s):  
Surface Area ◽  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Average Distance ◽  
Synthetic Data ◽  
Fast Method ◽  
3D Point Cloud ◽  
Partial Similarity ◽  
Distance Weighted

This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC). It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC) are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM) is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.

scholarly journals HIGH ACCURATE POINTWISE (GEO-)REFERENCING OF A K-TLS BASED MULTI-SENSOR-SYSTEM

2018 ◽  
Vol IV-4 ◽  
pp. 81-88 ◽  
Author(s):  
J. Hartmann ◽  
P. Trusheim ◽  
H. Alkhatib ◽  
J.-A. Paffenholz ◽  
D. Diener ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
High Accuracy ◽  
Laser Tracker ◽  
3D Point Cloud ◽  
Filter Model ◽  
Measurement Frequency ◽  
Set Up

<p><strong>Abstract.</strong> In recent years, the requirements in the industrial production, e.g., ships or planes, have been increased. In addition to high accuracy requirements with a standard deviation of 1<span class="thinspace"></span>mm, an efficient 3D object capturing is required. In terms of efficiency, kinematic laser scanning (k-TLS) has been proven its worth in recent years. It can be seen as an alternative to the well established static terrestrial laser scanning (s-TLS). However, current k-TLS based multi-sensor-systems (MSS) are not able to fulfil the high accuracy requirements. Thus, a new k-TLS based MSS and suitable processing algorithms have to be developed. In this contribution a new k-TLS based MSS will be presented. The main focus will lie on the (geo-)referencing process. Due to the high accuracy requirements, a novel procedure of external (geo-)referencing is used here. Hereby, a mobile platform, which is equipped with a profile laser scanner, will be tracked by a laser tracker. Due to the fact that the measurement frequency of the laser scanner is significantly higher than the measurement frequency of the laser tracker a direct point wise (geo-)referencing is not possible. To enable this a Kalman filter model is set up and implemented. In the prediction step each point is shifted according to the determined velocity of the platform. Because of the nonlinear motion of the platform an iterative extended Kalman filter (iEKF) is used here. Furthermore, test measurements of a panel with the k-TLS based MSS and with s-TLS were carried out. To compare the results, the 3D distances with the M3C2-algorithm between the s-TLS 3D point cloud and the k-TLS 3D point cloud are estimated. It can be noted, that the usage of a system model for the (geo-)referencing is essential. The results show that the mentioned high accuracy requirements have been achieved.</p>

scholarly journals GENERATION AND COMPARISON OF TLS AND SFM BASED 3D MODELS OF SOLID SHAPES IN HYDROMECHANIC RESEARCH

2016 ◽  
Vol XLI-B5 ◽  
pp. 925-929
Author(s):  
R. Zhang ◽  
D. Schneider ◽  
B. Strauß
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Accuracy Assessment ◽  
3D Models ◽  
3D Point Cloud ◽  
Synthetic Material ◽  
Qualitative Comparison ◽  
Software Packages ◽  
Main Influence

The aim of a current study at the Institute of Hydraulic Engineering and Technical Hydromechanics at TU Dresden is to develop a new injection method for quick and economic sealing of dikes or dike bodies, based on a new synthetic material. To validate the technique, an artificial part of a sand dike was built in an experimental hall. The synthetic material was injected, which afterwards spreads in the inside of the dike. After the material was fully solidified, the surrounding sand was removed with an excavator. In this paper, two methods, which applied terrestrial laser scanning (TLS) and structure from motion (SfM) respectively, for the acquisition of a 3D point cloud of the remaining shapes are described and compared. Combining with advanced software packages, a triangulated 3D model was generated and subsequently the volume of vertical sections of the shape were calculated. As the calculation of the volume revealed differences between the TLS and the SfM 3D model, a thorough qualitative comparison of the two models will be presented as well as a detailed accuracy assessment. The main influence of the accuracy is caused by generalisation in case of gaps due to occlusions in the 3D point cloud. Therefore, improvements for the data acquisition with TLS and SfM for such kind of objects are suggested in the paper.

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