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Reports (Research Report) Year : 2008

Principal Component Analysis in CGAL

Ankit Gupta
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Pierre Alliez
Sylvain Pion


Principal component analysis is a basic component of many geometric computing and processing algorithms. It is most commonly used on point sets, although applicable as well to sets of arbitrary primitives through the computation of covariance matrices. In this paper we provide closed form formulas of covariance matrices for sets of 2D and 3D geometric primitives such as segments, circles, triangles, iso rectangles, spheres, tetrahedra and iso cuboids. We also describe the method of deriving covariance matrices for their dimensional variants such as disks, balls etc. We finally discuss the flexibility and added value of the present approach by discussing its potential use in applications. Our implementation will be available through the next release of the CGAL library.
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Dates and versions

inria-00327027 , version 1 (07-10-2008)


  • HAL Id : inria-00327027 , version 1


Ankit Gupta, Pierre Alliez, Sylvain Pion. Principal Component Analysis in CGAL. [Research Report] RR-6642, INRIA. 2008, pp.13. ⟨inria-00327027⟩
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