Generalized quaternion interpolation

This MedLibrary.org supplementary page on Generalized quaternion interpolation is provided directly from the open source Wikipedia as a service to our readers. Please see the note below on authorship of this content, as well as the Wikipedia usage guidelines. To search for other content from our encyclopedia supplement, please use the form below:

Generalized quaternion interpolation is an interpolation method used by the slerp algorithm. It is closed-form and fixed-time, but it cannot be applied to the more general problem of interpolating more than two unit-quaternions.

Contents

Definition of unconstrained interpolation

General interpolation of unconstrained values \left\{ p \right\} with weights \left\{ w \right\} is defined as the value m that solves the sum

\sum_i w_i \left( p_i - m \right) = 0.

Because m and p values are unconstrained, this can be rewritten in the more familiar form of

m = wipi.
i

Quaternions, on the other hand, are constrained and the closed-form interpolation solution can not be applied to them.

Conversion to constrained interpolation

Because the unit-quaternion space is a closed Riemannian manifold, the difference between any two values on the manifold (in the tangent-space of the first value) can be defined as

d_{0,1} = \log \left( q_0^{-1} q_1 \right)

where the logarithm is the hypercomplex logarithm. This difference can be applied to the value in which it is a tangent-space member as

q_0 \exp \left( d_{0,1} \right) = q_1

where the hypercomplex exponential is used.

With these definitions in mind, the quaternion interpolation of values \left\{ q \right\} with weights \left\{ w \right\} can be defined (nearly identically to the unconstrained mean) as

\sum_i w_i \log \left( m^{-1} q_i \right) = 0

which says that the weighted sum of all differences to m (in m's tangent-space) is zero.

Recursive formulation

The quaternion mean value defined above can be found in a recursive algorithm with some initial estimate (one of the points, for example) that will halt when the net-error is below some threshold or the algorithm has iterated beyond some time limit.

Each iteration of the algorithm is as follows, with an initial mean estimate of m0

e_{k-1} = \sum_i w_i \log \left( m_{k-1}^{-1} q_i \right)
m_{k} = m_{k-1} \exp \left( e_{k-1} \right)

as iteration index k increases, the value mk will approach the true weighted-mean of the points.

References

  • Xavier Pennec, "Computing the mean of geometric features - Application to the mean rotation," Tech Report 3371, Institut National de Recherche en Informatique et en Automatique, March 1998.

Wikipedia content modification information:

  • This page was last modified on 15 July 2008, at 15:00.

Wikipedia Authorship and Review

Wikipedia content provided here is not reviewed directly by MedLibrary.org. Wikipedia content is authored by an open community of volunteers and is not produced by or in any way affiliated with MedLibrary.org.

Wikipedia Usage Guidelines

This article is licensed under the GNU Free Documentation License. It uses material from the Wikipedia article on "Generalized quaternion interpolation".

The URL for this specific entry is:

All Wikipedia text is available under the terms of the GNU Free Documentation License. (See Copyrights for details). Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc.