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 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 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.

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.

scholarly journals IDENTIFICATION OF INDIVIDUAL TREES AND GROUPS OF TREES IN THE LANDSCAPE USING AIRBORNE LASER SCANNING DATA

2014 ◽  
Vol 40 (3) ◽  
pp. 110-115 ◽  
Author(s):  
Robert Smreček ◽  
Zuzana Michňova
Keyword(s):  
Standard Deviation ◽  
Point Cloud ◽  
Laser Scanning ◽  
Average Distance ◽  
Aerial Images ◽  
3D Point Cloud ◽  
Average Difference ◽  
Airborne Laser ◽  
Fully Automatic ◽  
Individual Trees

In the work, a fully automatic approach for vegetation delineation using ALS data is presented. Nowadays, in Slovakia, aerial images and satellite scenes are used for this purpose. For vegetation identification, the measurement of local transparency and roughness directly in 3D point cloud was used. The aim was the identification of groups of trees with area bigger than 0.1 ha and individual trees. On the experimental area, 33 polygons representing groups of trees and 120 individual trees were identified. For groups of trees the accuracy of identification was 100%. For comparison, an area with reference polygons, which were manually vectorised by the operator on the orthophotos with spatial resolution 30 cm, was used. The average difference in the area was –0.26%, with standard deviation ±8.17%. The distance of borders of reference polygons and polygons derived from ALS data was also compared, average distance for border parts that fall inside the reference polygons was 2.24 m with standard deviation of ±2.8 m. The average distance for borders parts that fall outside of the reference polygons was 1.84 m with standard deviation ±2.04 m. The accuracy of individual trees identification was 98%.

scholarly journals Object-level Segmentation of RGBD Data

2014 ◽  
Vol II-3 ◽  
pp. 73-78 ◽  
Author(s):  
H. Huang ◽  
H. Jiang ◽  
C. Brenner ◽  
H. Mayer
Keyword(s):  
Global Optimization ◽  
Solid Body ◽  
Point Cloud ◽  
3D Model ◽  
3D Point Cloud ◽  
Indoor Scenes ◽  
Novel Method ◽  
3D Information ◽  
Object Level ◽  
Additional Channel

We propose a novel method to segment Microsoft™Kinect data of indoor scenes with the emphasis on freeform objects. We use the full 3D information for the scene parsing and the segmentation of potential objects instead of treating the depth values as an additional channel of the 2D image. The raw RGBD image is first converted to a 3D point cloud with color. We then group the points into patches, which are derived from a 2D superpixel segmentation. With the assumption that every patch in the point cloud represents (a part of) the surface of an underlying solid body, a hypothetical quasi-3D model – the "synthetic volume primitive" (SVP) is constructed by extending the patch with a synthetic extrusion in 3D. The SVPs vote for a common object via intersection. By this means, a freeform object can be "assembled" from an unknown number of SVPs from arbitrary angles. Besides the intersection, two other criteria, i.e., coplanarity and color coherence, are integrated in the global optimization to improve the segmentation. Experiments demonstrate the potential of the proposed method.

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.

The Application and Research of Terrestrial 3D Laser Scanning Technology in Tunnel Survey

2014 ◽  
Vol 709 ◽  
pp. 465-468
Author(s):  
Xian Quan Han ◽  
Fei Qin ◽  
Zhen Zhang ◽  
Shang Yi Yang
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
3D Model ◽  
Analysis Procedure ◽  
Surface Model ◽  
Point Cloud Data ◽  
3D Laser Scanning ◽  
Cloud Data ◽  
Experimental Application ◽  
Tunnel Section

This paper examines the basic flow and processing of the terrestrial 3D Laser scanning technology in the tunnel survey. The use of the method is discussed, point cloud data which have been registered, cropped can be constructed to a complete tunnel surface model. An example is given to extract the tunnel section and calculate the excavation of the tunnel. Result of the experimental application of this analysis procedure is given to illustrate the proposed technique can be flexibly used according to the need based on its 3D model. The feasibility and advantages of terrestrial 3D laser scanning technology in tunnel survey is also considered.

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