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[williamlai3a <>]

Hi,

I am testing the normal_estimation example on a 124915192 points point
cloud.
jet_fitting with k=34 finished smoothly,
but after that when attempting to run MST to orient the normals with K=34 (I
tried default18, same thing happens),
the algorithm eats all 64GB main memory and used up all 16GB swap space (in
ubuntu).
I am wondering if it is caused by storing a too big minimum spanning tree in
main memory?
Would further lower down the number of K helps? but would that trade off the
quality of the result?
Any advise?

Thank you very much.

William



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