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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.
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Definition of unconstrained interpolation
General interpolation of unconstrained values
with weights
is defined as the value m that solves the sum
.
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
where the logarithm is the hypercomplex logarithm. This difference can be applied to the value in which it is a tangent-space member as
where the hypercomplex exponential is used.
With these definitions in mind, the quaternion interpolation of values
with weights
can be defined (nearly identically to the unconstrained mean) as
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
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.
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