A computationally efficient approach to 3D point cloud reconstruction

2013 ◽  
Author(s):  
C.-H. Chang ◽  
N. Kehtarnavaz ◽  
K. Raghuram ◽  
R. Staszewski
Keyword(s):  
Point Cloud ◽  
3D Point Cloud ◽  
Computationally Efficient ◽  
Efficient Approach ◽  
3D Point Cloud Reconstruction

ADR-MVSNet: A Novel Cascade Network for 3D Point Cloud Reconstruction with Pixel Occlusion

2022 ◽  
pp. 108516
Author(s):  
Ying Li ◽  
Zhijie Zhao ◽  
Jiahao Fan ◽  
Wenyue Li
Keyword(s):  
Point Cloud ◽  
3D Point Cloud ◽  
3D Point Cloud Reconstruction

Per-pixel calibration using CALTag and dense 3D point cloud reconstruction

2019 ◽  
Author(s):  
Karelia Pena-Pena ◽  
Xiao Ma ◽  
Daniel L. Lau ◽  
Gonzalo R. Arce
Keyword(s):  
Point Cloud ◽  
3D Point Cloud ◽  
3D Point Cloud Reconstruction

scholarly journals Vegetation Removal on 3D Point Cloud Reconstruction of Cut-Slopes Using U-Net

2021 ◽  
Vol 12 (1) ◽  
pp. 395
Author(s):  
Ying Wang ◽  
Ki-Young Koo
Keyword(s):  
Image Segmentation ◽  
Point Cloud ◽  
Point Clouds ◽  
3D Point Cloud ◽  
Cut Slope ◽  
Index Method ◽  
Vegetation Removal ◽  
3D Point Cloud Reconstruction ◽  
Cut Slopes ◽  
Projection Matrices

The 3D point cloud reconstruction from photos taken by an unmanned aerial vehicle (UAV) is a promising tool for monitoring and managing risks of cut-slopes. However, surface changes on cut-slopes are likely to be hidden by seasonal vegetation variations on the cut-slopes. This paper proposes a vegetation removal method for 3D reconstructed point clouds using (1) a 2D image segmentation deep learning model and (2) projection matrices available from photogrammetry. For a given point cloud, each 3D point of it is reprojected into the image coordinates by the projection matrices to determine if it belongs to vegetation or not using the 2D image segmentation model. The 3D points belonging to vegetation in the 2D images are deleted from the point cloud. The effort to build a 2D image segmentation model was significantly reduced by using U-Net with the dataset prepared by the colour index method complemented by manual trimming. The proposed method was applied to a cut-slope in Doam Dam in South Korea, and showed that vegetation from the two point clouds of the cut-slope at winter and summer was removed successfully. The M3C2 distance between the two vegetation-removed point clouds showed a feasibility of the proposed method as a tool to reveal actual change of cut-slopes without the effect of vegetation.

scholarly journals 3D point cloud reconstruction from single plenoptic image

2016 ◽  
Vol 8 (1) ◽  
pp. 26-31 ◽  
Author(s):  
Francesca Murgia ◽  
Cristian Perra ◽  
Daniele Giusto
Keyword(s):  
Point Cloud ◽  
3D Point Cloud ◽  
3D Point Cloud Reconstruction

Time-of-Flight camera based 3D point cloud reconstruction of a car

2013 ◽  
Vol 64 (9) ◽  
pp. 1099-1114 ◽  
Author(s):  
Thomas Hoegg ◽  
Damien Lefloch ◽  
Andreas Kolb
Keyword(s):  
Point Cloud ◽  
Time Of Flight ◽  
3D Point Cloud ◽  
3D Point Cloud Reconstruction
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