CODEWITHSUNDEEP
c++
slinga
slinga

Reputation: 57

RANSAC line3d fitting by 3d line segments

I am having many 3d line segments. some of them are nearly parallel and some are oriented in to different direction. I want to avoid outliers and to get the best line 3d to represent the given 3d line segments.

I am bit confused how RANSAC method apply for this case...

should i find a random line first or should i consider this as a given 3d point problem.?

can anyone post me the stucture to be followed when implenting this in c++. thanks

Upvotes: 0

Views: 1684

Answers (1)

ChronoTrigger
ChronoTrigger

Reputation: 8617

RANSAC is a good tool to fit data to a model. If you had a single 3D line in a collection of segments, by running RANSAC and selecting the line that maximized the amount of inliers would be enough. However, since you have many lines in the collection, you should try a different approach (even a non-RANSAC one, as I tell you later).

For example, you can run first RANSAC trying to find the line that matches as many segments as possible. After finding that line, remove the inlier segments from the collection and run RANSAC again.

To create a line, you only need a segment, so building the line model is quite easy.

To decide on whether a segment fits a line, you may compute the angle between both with the dot product (the closer to 0 the better) and the distance from the middle point of the segment to the line.

Also note that you can filter out very small segments at as first step. You could save some iterations later and avoid noisy results.

I can think of a Hough transform approach as well. Since you can create a line from each segment, you can get the parameters of its line (normal or directional vector and distance to origin), quantize them to some acceptable bin-size and add a vote to those parameters in a matrix. Finally, your lines lie in the peaks of the vote matrix.

Upvotes: 1

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