For the 3D point cloud data aquired by laser scanning measurement of ship block, an efficient denoising algorithm based on image and normal vector threshold judgement is proposed. Firstly, large scale noise points are eliminated using global threshold judgement based image, then Kuwahara filter algorithm is used for data smoothing and a denoising algorithm based on normal vector threshold judgement is proposed to eliminate noises point excluding ship manufacture sections. The experiment result demonstrates that not only the proposed denoising algorithm keeps key data points but also avoids bluring point cloud boundary and eliminates noise points effectively
Point cloud data has been one type of widely used data sources in the field of remote sensing. Key s...
To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the...
This work presents a new method that automatically detects and analyzes surface defects such as corr...
For the 3D point cloud data aquired by laser scanning measurement of ship block, an efficient denois...
In three-dimensional (3D) shape measurement based on fringe projection, various factors can degrade ...
Recent advancement in scanning technologies has allowed an object to be represented in the 3D point ...
International audienceThe noise data could be produced when we scanned the object by Handy 3D scanne...
This paper proposes a single-stage adaptive multi-scale noise filtering algorithm for point clouds, ...
The effect of point cloud denoising is very important to the subsequent surface fitting and modeling...
International audienceLight fields are 4D signals capturing rich information from a scene. The avail...
International audienceSince the advantages of low cost and high efficiency, the three dimensional po...
Block-matching and 3D filtering (BM3D) denoising algorithm [1] proposed recently has a problem of co...
A point cloud that is obtained by an RGB-D camera will inevitably be affected by outliers that do no...
Part 3: PostersInternational audienceThe reconstruction and visualization of three-dimensional point...
Three-dimensional models are usually a severe simplification of the real world. Laser scans that are...
Point cloud data has been one type of widely used data sources in the field of remote sensing. Key s...
To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the...
This work presents a new method that automatically detects and analyzes surface defects such as corr...
For the 3D point cloud data aquired by laser scanning measurement of ship block, an efficient denois...
In three-dimensional (3D) shape measurement based on fringe projection, various factors can degrade ...
Recent advancement in scanning technologies has allowed an object to be represented in the 3D point ...
International audienceThe noise data could be produced when we scanned the object by Handy 3D scanne...
This paper proposes a single-stage adaptive multi-scale noise filtering algorithm for point clouds, ...
The effect of point cloud denoising is very important to the subsequent surface fitting and modeling...
International audienceLight fields are 4D signals capturing rich information from a scene. The avail...
International audienceSince the advantages of low cost and high efficiency, the three dimensional po...
Block-matching and 3D filtering (BM3D) denoising algorithm [1] proposed recently has a problem of co...
A point cloud that is obtained by an RGB-D camera will inevitably be affected by outliers that do no...
Part 3: PostersInternational audienceThe reconstruction and visualization of three-dimensional point...
Three-dimensional models are usually a severe simplification of the real world. Laser scans that are...
Point cloud data has been one type of widely used data sources in the field of remote sensing. Key s...
To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the...
This work presents a new method that automatically detects and analyzes surface defects such as corr...