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Explain how to use Error Quadrics to compute the closest point to a set of planes!
We can represent a plane by
if
and a point by
Then, the distance from to the plane is given by
Given a set of planes , we want to find a point which minimizes the squared distances to all planes:
The matrices are called fundamental error quadrics and are computed as
From this definition, we see that the error quadrics of two sets of planes , can simply be merged into one error quadric by adding them:
Solution Approach 1
In order to find a minimum solution for , we can find the eigenvector to the smallest eigenvalue of .
Solution Approach 2
By computing
we obtain the linear system
Which is easier to solve than computing the eigenvectors and eigenvalues of .
if
and a point by
Then, the distance from to the plane is given by
Given a set of planes , we want to find a point which minimizes the squared distances to all planes:
The matrices are called fundamental error quadrics and are computed as
From this definition, we see that the error quadrics of two sets of planes , can simply be merged into one error quadric by adding them:
Solution Approach 1
In order to find a minimum solution for , we can find the eigenvector to the smallest eigenvalue of .
Solution Approach 2
By computing
we obtain the linear system
Which is easier to solve than computing the eigenvectors and eigenvalues of .
Karteninfo:
Autor: janisborn
Oberthema: Informatik
Thema: Computergrafik
Schule / Uni: RWTH Aachen
Ort: Aachen
Veröffentlicht: 18.05.2022