@@bohdangutnyk8222 So when reading the graph, is the blue area the "flat" area and the green and yellow areas the areas that aren't flat? I am just having trouble trying to relate the scalar field/values to what is actually being represented.
@@sethshaver8840 Not quite right. The color of the scalar field shows the distance from the point cloud to the reference plane. In your case, if the point cloud is colored green, it means that it is flat and lies a short distance to the reference plane. In areas where you have irregularities, the point cloud should turn blue or red, depending on the side of the deviation from the base plane (plus or minus height). You can send me your data in Dropbox and I will record new video with more explanation.
I have a question regarding the term deformation. You meant by deformation is that missing point clouds from the laser scan or missing parts of the building, like damaged wall due to the age of the building and we can fix that? Because my senior project is to fix the deformations in the building and i want know the meaning
Thank you very much for this video. I have a question regarding the colors - do the colors indicate that an object on the football field move on a certain axis? I mean, the color scale shows the positive or negative distances to the reference, but are the calculations based on the z axis or one of the other two?
Thanks for your feedback, you can read little more about calculation distances in cloudcompare wiki, here is a link www.cloudcompare.org/doc/wiki/index.php?title=Distances_Computation
These distances between a specified surface and a point cloud are stored in the point cloud as a separate Scallar field, similar to intensity. They can also be written as RGB colors. To do this, Cloud compare has a separate function - Edit>Scalar field>Convert to RGB. After that, you can load the point cloud in Potree Viewer and see this Scalar field
Thanks for your efforts I am still a beginner, and I have a project that I am currently working on, which is that I made a model on AutoCAD, and then after that I made it manually, which is a foot scanning device, and I actually scanned the foot several times on the Scanniverse program and extracted them as obj files now I have to use cloudcompare software to carry out a target/actual comparison and measure the deviations of the individual scans. how i can do this please. If you can make a short Video i will be very thankful Thank you in advance
First of all thank you for sharing your knowledge. Very good video. I have a question. How would you overlay these results on CAD with the project (drawing)? I think it would be more visible and better if you overlay these results with CAD drawing so that we see which part of stadium exactly.
Thanks for the comments, I appreciate that. In my opinion, one of the methods to show this in AutoCAD is to create contours lines from the point cloud with a step of 0.05-0.1 m between the lines. In places where the field is deformed, contours lines will be curved or with not the same distance between each other. Another way, is to export this point cloud as raster image and use this image as underlay in your AutoCAD drawing.
Just import them to cloudcompare and press "compute cloud to cloud distance"(button to the left from which I use in the video). The rest of workflow will be the same.
The sign distance is not available for cloud 2 cloud distance; only for cloud to model or model to model because the sign distance is being estimated based on the mesh triangles' normals. I think the best approach is to mesh your point cloud data and then estimate the sign distance.
Perhaps you can find an additional plugin to work with lidar data. The standard functions of the Arg GIS pro can be not enough. You can also experiment with displaying a point cloud using a height gradient.
Thank you for answering my question! You are my hero
You're Welcome
@@bohdangutnyk8222 So when reading the graph, is the blue area the "flat" area and the green and yellow areas the areas that aren't flat? I am just having trouble trying to relate the scalar field/values to what is actually being represented.
@@sethshaver8840 Not quite right. The color of the scalar field shows the distance from the point cloud to the reference plane. In your case, if the point cloud is colored green, it means that it is flat and lies a short distance to the reference plane. In areas where you have irregularities, the point cloud should turn blue or red, depending on the side of the deviation from the base plane (plus or minus height). You can send me your data in Dropbox and I will record new video with more explanation.
I have a question regarding the term deformation. You meant by deformation is that missing point clouds from the laser scan or missing parts of the building, like damaged wall due to the age of the building and we can fix that? Because my senior project is to fix the deformations in the building and i want know the meaning
Thank you very much for this video. I have a question regarding the colors - do the colors indicate that an object on the football field move on a certain axis? I mean, the color scale shows the positive or negative distances to the reference, but are the calculations based on the z axis or one of the other two?
Thanks for your feedback, you can read little more about calculation distances in cloudcompare wiki, here is a link www.cloudcompare.org/doc/wiki/index.php?title=Distances_Computation
Great video. Is there a way to see7visualize both rgb and deviations map in same point cloud in point cloud viewers like Potree or similar?
These distances between a specified surface and a point cloud are stored in the point cloud as a separate Scallar field, similar to intensity. They can also be written as RGB colors. To do this, Cloud compare has a separate function - Edit>Scalar field>Convert to RGB. After that, you can load the point cloud in Potree Viewer and see this Scalar field
@bohdangutnyk8222 Thank you very much for fast reply. Is there any specific export option or format which will keep scalar field as it is?
Thanks for your efforts
I am still a beginner, and I have a project that I am currently working on, which is that I made a model on AutoCAD, and then after that I made it manually, which is a foot scanning device, and I actually scanned the foot several times on the Scanniverse program and extracted them as obj files now I have to use cloudcompare software to carry out a target/actual comparison and measure the deviations of the individual scans.
how i can do this please.
If you can make a short Video i will be very thankful
Thank you in advance
First of all thank you for sharing your knowledge. Very good video. I have a question. How would you overlay these results on CAD with the project (drawing)? I think it would be more visible and better if you overlay these results with CAD drawing so that we see which part of stadium exactly.
Thanks for the comments, I appreciate that. In my opinion, one of the methods to show this in AutoCAD is to create contours lines from the point cloud with a step of 0.05-0.1 m between the lines. In places where the field is deformed, contours lines will be curved or with not the same distance between each other.
Another way, is to export this point cloud as raster image and use this image as underlay in your AutoCAD drawing.
Thank you for video! Could you help me? I d'like to do analys deformation of wall (or any vetical construction)? I coudn't
just follow what I show in the video. Workflow for vertical surfaces is exactly the same as for this football field
I have two point clouds, and I want to calculate the sign distance between those two, not point to mesh but point to point. How can I do that?
Just import them to cloudcompare and press "compute cloud to cloud distance"(button to the left from which I use in the video). The rest of workflow will be the same.
@@bohdangutnyk8222 in that part I can not click sign distance. Its shadowed. Only absolute distance is shown.
Have you selected both point clouds on the left panel(DB tree)?
@@bohdangutnyk8222 yes. I selected both cloud. Then click the cloud to cloud distance. The sign distance option is shadowed over there.
The sign distance is not available for cloud 2 cloud distance; only for cloud to model or model to model because the sign distance is being estimated based on the mesh triangles' normals. I think the best approach is to mesh your point cloud data and then estimate the sign distance.
is this task also possible to be done in Arc GIS Pro ?
Perhaps you can find an additional plugin to work with lidar data. The standard functions of the Arg GIS pro can be not enough. You can also experiment with displaying a point cloud using a height gradient.