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How to fit a 3D plane Pi on some binary image points using SVD and RANSAC and then finding the main axis by applying PCA on the obtained 3D points?

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PRACHI SHARMA on 12 Aug 2019
Commented: PRACHI SHARMA on 12 Aug 2019
I am trying to implement a paper -
'Combining multiple depth-based descriptors for hand gesture
recognition' by Fabio Dominio, Mauro Donadeo, Pietro Zanuttigh
I am pasting a line from a paragraph under 'Hand Segmentation' of the paper (Page no. 104)-
"Once all the possible palm samples have been detected, we fit a
3D plane p on them by using SVD and RANSAC. Then Principal
Component Analysis (PCA) is applied to the 3D points in H in order
to extract the main axis that roughly corresponds to the direction
ix of the vector going from the wrist to the fingertips. "
According to the paper, I now have hand palm samples but I am not able to understand how to implement the above mentioned part. It is a big paragraph so I have pasted just the first few lines of it.
I have attached the paper PDF with this question. If anybody has any idea regarding the same whether in MATLAB or Python, please let me know.
Thanks in advance!

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