Introduction to algorithms
Feature-based image metamorphosis
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Diffeomorphisms Groups and Pattern Matching in Image Analysis
International Journal of Computer Vision
Variational problems on flows of diffeomorphisms for image matching
Quarterly of Applied Mathematics
Group Actions, Homeomorphisms, and Matching: A General Framework
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: Part II
Variational Methods for Multimodal Image Matching
International Journal of Computer Vision
IEEE Computer Graphics and Applications
Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms
International Journal of Computer Vision
Texture transfer during shape transformation
ACM Transactions on Graphics (TOG)
Geodesic image normalization and temporal parameterization in the space of diffeomorphisms
Miar'06 Proceedings of the Third international conference on Medical Imaging and Augmented Reality
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
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We develop a practical, symmetric, data-driven formulation, geodesic image interpolation (GII), for interpolating images with respect to geometric and photometric variables. GII captures, in implementation, the desirable properties of symmetry that comes from the theory of diffeomorphisms and Grenander’s computational anatomy (CA). Geodesic diffeomorphisms are a desirable transformation model as they provide a symmetric deforming path connecting images or a series of images. Once estimated, this geodesic may be used to (re)parameterize and interpolate image sets in approximation of continuous, deforming dynamic processes. One may then closely recover the original continuous signal from a few samples. The method, based on our work in symmetric diffeomorphic image registration, generalizes the concept of point set reparameterization to the case where point sets are replaced by image sets. This problem differs from point reparameterization in that a variational image correspondence problem must be solved before resampling. Our image reparameterization method is applied to solve similar problems to point reparameterization: dense interpolation, matching and simulation of dynamic processes are illustrated.