Hello,
I've been using the ground filtering algorithm with great success so far but I was wondering how accurate it was. I ran a few tests using sample data and creating confusion matrices, comparing the results with state-of-the-art algorithms to assess his performance. So far so good.
As a student doing his masters thesis, I'd love to know a bit more about how it works. I understand, as a commercial licence, that I won't get much, but it's worth a try!
In the User Manual, it is written:
Max angle (deg)
Determines one of the conditions to be checked while testing a point as a ground one, i.e. sets limitation for an angle between terrain model and the line to connect the point in question with a point from a ground class. For nearly flat terrain it is recommended to use default value of 15 deg for the parameter. It is reasonable to set a higher value, if the terrain contains steep slopes.
Max distance (m)
Determines one of the conditions to be checked while testing a point as a ground one, i.e. sets limitation for a distance between the point in question and terrain model. In fact, this parameter determines the assumption for the maximum variation of the ground elevation at a time.
Cell size (m)
Determines the size of the cells for point cloud to be divided into as a preparatory step in ground points classification procedure. Cell size should be indicated with respect to the size of the largest area within the scene that does not contain any ground points, e. g. building or close forest.
- Where is the algorithm starting? Most algorithms assume the lowest point is a ground point and start from here. Is it the same case here?
- I guess it deals with outliers using a combination of two criterion: Max Angle & Max Distance. But what if the lowest local point happens to be an outlier? Do you run some kind of SOR filter prior to the lowest point picking?
Any answer is appreciated!
Topic: Ground filtering algorithm: where does it start? (Read 1825 times)
