Mixture of Probabilistic Principal Component Analyzers for Shapes from Point Sets

software

posted on 2017-06-20, 16:43 authored by Ali Gooya, Alejandro FrangiAlejandro Frangi, Jose Pozo Soler

This Matlab class computes a Mixture of Probabilistic Principal Component Analysers from spatial point clouds with no point-to-point correspondences.

If the point clouds represent shapes, the model generates clusters of shape
atlases, computing mean shape and modes of variations in each cluster of shapes. The naming convention of the variables and the details of the model has been described in the following paper:

"Mixture of Probabilistic Principal Component Analyzers for Shapes from Point Sets" DOI 10.1109/TPAMI.2017.2700276, IEEE Transactions on Pattern Analysis and Machine Intelligence (in press)

A test data set, including point sets from 50 vertebrae models has been included for a quick start under the folder 'SamplePointSets'.

Please refer to the included 'README.md' file the for further details on how to run the model. There is no dependencies other than Matlab.

Funding

Marie-Curie IIF, (Contract Agreement 625745), granted to A. Gooya

History

Ethics

There is no personal data or any that requires ethical approval

Policy

The data complies with the institution and funders' policies on access and sharing

Sharing and access restrictions

The data can be shared openly

Data description

The file formats are open or commonly used

Methodology, headings and units

There is a readme.txt file describing the methodology, headings and units

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Keywords

Mixture Principal Component Analyzers Shapes from Point Clouds Computer Engineering

Licence

MIT

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