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- #Find best trainslation point cloud different size how to#
- #Find best trainslation point cloud different size free#
There are a few ways of finding optimal rotations between points. This bit is easy, the centroids are just the average of the points and can be calculated as follows:Īnd are 3×1 vectors eg. Bring both dataset to the origin then find the optimal rotation R.R is a 3×3 rotation matrix and t is the translation vector (technically matrix Nx3).įinding the optimal rigid transformation matrix can be broken down into the following steps: Where A and B are sets of 3D points with known correspondences. If the data is noisy it will minimize the least squares error A minimum of 3 unique points is required for a unique solution.
#Find best trainslation point cloud different size free#
The solution presented will work with both noise free and noisy data. This problem arises especially in tasks like 3D point cloud data registration, where the data is obtained from hardware like a 3D laser scanner or the popular Kinect device. This is in contrast to an affine transform, which includes scaling and shearing. This transformation is sometimes called the Euclidean or Rigid transform, because it preserves the shape and size. Here, ‘optimal’ or ‘best’ is in terms of least square errors. We want to find the best rotation and translation that will align the points in dataset A to dataset B. The corresponding points have the same colour, R is the rotation and t is the translation. An illustration of the problem is shown below for the simplest case of 3 corresponding points (the minimum required points to solve). Starting from there I should be able to rotate my cloud, then crop it further to reduce it more precisely to my AOI and then rotate it back so I have again a georeferenced cloud.Finding the optimal/best rotation and translation between two sets of corresponding 3D point data, so that they are aligned/registered, is a common problem I come across. I guess if I set the shift of x and y both to 0, my point cloud would be at the origin, right? The problem I might have, is that the automatic translation did not set my point cloud to the origin of the coordinate system.
#Find best trainslation point cloud different size how to#
I have to look it up this week how to do so, but something I learned long time ago in school might help :). If the rotation is around the coordinate system origin as you explained it I should be able to calculate the new coordinates with some vector calculations. Since the global shift is stored and restored at export time, I'm okay with this. But CloudCompare did a translation (global shift) before opening the file, because my x and y values are pretty big. So I guess my AOI is in a real world coordinate system.
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The data I have is georeferenced, and to my knwoledge there were used seven ground control points used during the 146 scans of the entire plot. Thank you for your quick reply, it seems I missed it, I'm sorry for the long delay. starting roughly there where the points in the lower left corner are visable (actually I need to crop a few meters to the right)Įdit: sorry for the doubble post, I forgot to attach the picturesĠ2_Rotated.jpeg (128.31 KiB) Viewed 4436 times 01_original.jpeg (137.31 KiB) Viewed 4436 times The second one is the same as above but rotated ~12 degrees, now I want to crop the point cloud again. In the middle u can see a quite straight line of rails were a crane is attached Pictures: First one displays just two out of the 146 scans of the plot, but the plot size is displayed by the bounding box.
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In my use case it would be nice if it would rotate around my lower left corner so at least that coordinate wouldn't change.Ī) crop a point cloud with an polygonal shape to my exact coordinates of my plot orī) to rotate the cloud and then somehow calculate the new relative position of my coordinates. Now a have a rotated cloud, but it seems that the rotation was done around the center of the bounding shape (just guessing).īecause if I try to crop the cloud by my coordinates of my AOI, it wouldn't crop at the expected position. I solved this by using the Edit/Apply transformation (alt+t) and using the calculated correction angle (in this case ~12 degrees, see Picture two). The only problem I encountered so far is that my plot isn't orthogonal to the coordinate-system. Basically I want to crop my point cloud to those coordinates. The data is geo-referenced and I do have the exact coordinates of my AOI. To reduce the data I try to focus only to the area of interest (AOI). I have a huge plot (over 1 hectar) of trees scanned. I recently started to work with point clouds from TLS - Data.