Denoising of a Multi-Station Point Cloud and 3D Modeling Accuracy for Substation Equipment Based on Statistical Outlier Removal

2020 ◽  
Author(s):  
Jianlong Guo ◽  
Weixia Feng ◽  
Tengfei Hao ◽  
Peng Wang ◽  
Shuang Xia ◽  
...  
Keyword(s):  
3D Modeling ◽  
Point Cloud ◽  
Outlier Removal ◽  
Modeling Accuracy ◽  
Substation Equipment ◽  
Station Point

3D Modeling Approach of Building Construction based on Point Cloud Data Using LiDAR

2019 ◽  
Author(s):  
Byeongjun Oh ◽  
Minju Kim ◽  
Chanwoo Lee ◽  
Hunhee Cho ◽  
Kyung-In Kang
Keyword(s):  
3D Modeling ◽  
Point Cloud ◽  
Building Construction ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Modeling Approach

scholarly journals Registration of Multi-Sensor Bathymetric Point Clouds in Rural Areas Using Point-to-Grid Distances

2019 ◽  
Vol 8 (4) ◽  
pp. 178 ◽  
Author(s):  
Richard Boerner ◽  
Yusheng Xu ◽  
Ramona Baran ◽  
Frank Steinbacher ◽  
Ludwig Hoegner ◽  
...  
Keyword(s):  
Rural Areas ◽  
Point Cloud ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Target Point ◽  
Outlier Removal ◽  
Least Squares Optimization ◽  
Rotation Parameters ◽  
Airborne Sensors ◽  
Fine Registration

This article proposes a method for registration of two different point clouds with different point densities and noise recorded by airborne sensors in rural areas. In particular, multi-sensor point clouds with different point densities are considered. The proposed method is marker-less and uses segmented ground areas for registration.Therefore, the proposed approach offers the possibility to fuse point clouds of different sensors in rural areas within an accuracy of fine registration. In general, such registration is solved with extensive use of control points. The source point cloud is used to calculate a DEM of the ground which is further used to calculate point to raster distances of all points of the target point cloud. Furthermore, each cell of the raster DEM gets a height variance, further addressed as reconstruction accuracy, by calculating the grid. An outlier removal based on a dynamic threshold of distances is used to gain more robustness against noise and small geometry variations. The transformation parameters are calculated with an iterative least-squares optimization of the distances weighted with respect to the reconstruction accuracies of the grid. Evaluations consider two flight campaigns of the Mangfall area inBavaria, Germany, taken with different airborne LiDAR sensors with different point density. The accuracy of the proposed approach is evaluated on the whole flight strip of approximately eight square kilometers as well as on selected scenes in a closer look. For all scenes, it obtained an accuracy of rotation parameters below one tenth degrees and accuracy of translation parameters below the point spacing and chosen cell size of the raster. Furthermore, the possibility of registration of airborne LiDAR and photogrammetric point clouds from UAV taken images is shown with a similar result. The evaluation also shows the robustness of the approach in scenes where a classical iterative closest point (ICP) fails.

Point Cloud Noise and Outlier Removal for Image-Based 3D Reconstruction

2016 ◽  
Author(s):  
Katja Wolff ◽  
Changil Kim ◽  
Henning Zimmer ◽  
Christopher Schroers ◽  
Mario Botsch ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Outlier Removal

scholarly journals EVALUATING THE POTENTIAL OF IMAGING ROVER FOR AUTOMATIC POINT CLOUD GENERATION

2017 ◽  
Vol XLII-2/W3 ◽  
pp. 147-154 ◽  
Author(s):  
V. Cera ◽  
M. Campi
Keyword(s):  
3D Modeling ◽  
Interdisciplinary Research ◽  
Point Cloud ◽  
Survey Techniques ◽  
Advantages And Disadvantages ◽  
Integrated Methodology ◽  
Ideal Approach ◽  
Ancient Site ◽  
Single Instrument ◽  
The Ideal

The paper presents a phase of an on-going interdisciplinary research concerning the medieval site of Casertavecchia (Italy). The project aims to develop a multi-technique approach for the semantic - enriched 3D modeling starting from the automatic acquisition of several data. <br><br> In particular, the paper reports the results of the first stage about the Cathedral square of the medieval village. The work is focused on evaluating the potential of an imaging rover for automatic point cloud generation. Each of survey techniques has its own advantages and disadvantages so the ideal approach is an integrated methodology in order to maximize single instrument performance. <br><br> The experimentation was conducted on the Cathedral square of the ancient site of Casertavecchia, in Campania, Italy.

scholarly journals UNDERWATER 3D MODELING: IMAGE ENHANCEMENT AND POINT CLOUD FILTERING

2016 ◽  
Vol XLI-B2 ◽  
pp. 441-447 ◽  
Author(s):  
I. Sarakinou ◽  
K. Papadimitriou ◽  
O. Georgoula ◽  
P. Patias
Keyword(s):  
Image Enhancement ◽  
3D Modeling ◽  
Point Cloud ◽  
3D Models ◽  
Main Process ◽  
Ongoing Research ◽  
Different Depths ◽  
The Creation ◽  
Geometric Quality

This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images’ radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

scholarly journals 3D modeling of an object located in the underwater robot’s manipulator workspace using a point cloud

2020 ◽  
Vol 539 ◽  
pp. 012123
Author(s):  
L Astapova ◽  
A Korsakov ◽  
E Smirnova ◽  
A Gabriel ◽  
V Ulanov
Keyword(s):  
3D Modeling ◽  
Point Cloud

scholarly journals A Fuzzy Comprehensive Evaluation Approach for the 3D Modeling Accuracy of UAV Oblique Photogrammetry

2021 ◽  
Vol 693 (1) ◽  
pp. 012045
Author(s):  
Zhaohu Zhang ◽  
Yongzhi Zhang ◽  
Zhaojun Yong ◽  
Jinzheng Liang ◽  
Xinyang Ye ◽  
...  
Keyword(s):  
3D Modeling ◽  
Comprehensive Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Evaluation Approach ◽  
Modeling Accuracy
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