Can anyone explain the difference between organized and unorganized point cloud?

Question

What is the difference between organized point cloud and an unorganized one?

Am I right in thinking that a point cloud is a column of [x,y,z] values? Than what is the difference in the structure of the point cloud if its organized or unorganized ?

How does it affect the later processing steps like filtering, normal estimation, registration etc ?

Thanks, Sai

Execratory

Answer 1

See the notes on this page on HEIGHT and WIDTH of a point cloud: Point Cloud File Format

An organised point cloud is organized as a 2D array of points with the same properties you'd expect if the points were obtained from a projective camera, like the Kinect, DepthSense or SwissRanger. In PCL the points array of a point cloud is actually a 2D array but one of those dimensions is only used for representing organised point clouds.

In both organised and unorganised point clouds, all of X Y and Z are provided for each point, but the memory layout of organised point clouds is that of a 2D array. The memory layout of the points then is closely related to the spatial layout as represented by these XYZ values.

Algorithms that work on unorganised point clouds will generally work on organised point clouds (since the 2D array of points is packed and can be interpreted as a 1D array) but specialised algorithms can be designed to work on organized point clouds. An example is the use of the organized property of a point cloud to speed up the process of calculating normals: Integral Images Normal Estimation Tutorial

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Updated links: (1) pcl.readthedocs.io/projects/tutorials/en/latest/… (2) pcl.readthedocs.io/projects/tutorials/en/latest/… – Dishonest

Answer 2

Organized point cloud data use 2D array for future implementations.

Unorganized point cloud data has height = 1 i.e. it is a 1D array.

Exert

Answer 3

As in the PCL document, WIDTH can indicate the differences:
WIDTH - specifies the width of the point cloud dataset in the number of points. WIDTH has two meanings:

1. it can specify the total number of points in the cloud for unorganized datasets;
2. it can specify the width (total number of points in a row) of an organized point cloud dataset.

An unorganized point cloud is in form of a 1D array, hence the height is 1; while the organized cloud is in form of a 2D array, its number of points is equal to WIDTH * HEIGHT

Reference: The PCD (Point Cloud Data) file format

Aversion

THIS, is the most clearest explanation of them all. Thank you. – Arrow

Answer 4

1,Organized point clouds are most from depth images, while the unorganized are from Ladar scanning or others technology;

2,The organized point clouds are like 2D image, it has width and height, it is ordered and can be retrieved by the index of each point.Unorganized point clouds is listed in 1D array, its height is 1, its width is the number of points. It is orderless, you cannot find the specified point.For this reason, some tasks are time consuming using the unorganized point clouds.

3, from the pcl tutorial. “Unorganized” point clouds are characterized by non-existing point references between points from different point clouds due to varying size, resolution, density and/or point ordering. In case of “organized” point clouds often based on a single 2D depth/disparity images with fixed width and height, a differential analysis of the corresponding 2D depth data might be faster.

Humiliating