direct_gmm
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Project code for "Direct Fitting of Gaussian Mixture Models"
Direct Fitting of GMMs project website
This is the source code and project history for the following publication
Direct Fitting of Gaussian Mixture Models by Leonid Keselman and Martial Hebert (arXiv version here)
Overview
Almost all files used in the development and testing of this project are in this folder. The data files for the Stanford Bunny is included in bunny
.
-
mixture
contains the modifed version of scikit-learn with the proposed techniques. -
gmm_fit.py
andgmm_fit2.py
contain the two sets of the bunny likelihood experiments -
registration_test.py
contains the mesh registration (P2D) experiments - Files with
_extra
are usually just copies for non-Stanford Bunny experiments -
gen_gmm.ipynb
andgen_gmm_mine.ipynb
generate GMM models from the TUM dataset, with and without uncertainty models -
reg_results.ipynb
performs D2D registration between the GMM models built from the TUM dataset.