Title
Real-Time Nonlinear Shape Interpolation
Abstract
We introduce a scheme for real-time nonlinear interpolation of a set of shapes. The scheme exploits the structure of the shape interpolation problem, in particular the fact that the set of all possible interpolated shapes is a low-dimensional object in a high-dimensional shape space. The interpolated shapes are defined as the minimizers of a nonlinear objective functional on the shape space. Our approach is to construct a reduced optimization problem that approximates its unreduced counterpart and can be solved in milliseconds. To achieve this, we restrict the optimization to a low-dimensional subspace that is specifically designed for the shape interpolation problem. The construction of the subspace is based on two components: a formula for the calculation of derivatives of the interpolated shapes and a Krylov-type sequence that combines the derivatives and the Hessian of the objective functional. To make the computational cost for solving the reduced optimization problem independent of the resolution of the example shapes, we combine the dimensional reduction with schemes for the efficient approximation of the reduced nonlinear objective functional and its gradient. In our experiments, we obtain rates of 20--100 interpolated shapes per second, even for the largest examples which have 500k vertices per example shape.
Year
DOI
Venue
2015
10.1145/2729972
ACM Trans. Graph.
Keywords
Field
DocType
algorithms,geometric modeling,geometric optimization,geometry processing,interactive tools,model reduction,physically based modeling,shape averaging,shape interpolation
Computer vision,Nonlinear system,Nonlinear interpolation,Geometry processing,Geometric modeling,Interpolation,Algorithm,Artificial intelligence,Mathematics
Journal
Volume
Issue
ISSN
34
3
0730-0301
Citations 
PageRank 
References 
19
0.58
32
Authors
4
Name
Order
Citations
PageRank
Christoph von Tycowicz118310.31
Christian Schulz221310.71
Hans-Peter Seidel312532801.49
Klaus Hildebrandt446624.77