Oren Freifeld

Senior Academic

Highly-expressive spaces of well-behaved transformations

Keeping it simple

Oren Freifeld, Soren Hauberg, Kayhan Batmanghelich, John W. Fisher

We propose novel finite-dimensional spaces of Rn ? Rn transformations, n ? {1, 2, 3}, derived from (continuously-defined) parametric stationary velocity fields. Particularly, we obtain these transformations, which are diffeomorphisms, by fast and highly-accurate integration of continuous piecewise-affine velocity fields, we also provide an exact solution for n = 1. The simple-yet-highly-expressive proposed representation handles optional constraints (e.g., volume preservation) easily and supports convenient modeling choices and rapid likelihood evaluations (facilitating tractable inference over latent transformations). Its applications include, but are not limited to: unconstrained optimization over monotonic functions, modeling cumulative distribution functions or histograms, time warping, image registration, landmark-based warping, real-time diffeomorphic image editing. Our code is available at https://github.com/freifeld/cpabDiffeo.

Publication language English
Pages 2911-2919
Publication status Published - 17.02.2015
Article Number 7410690

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Access to Document
10.1109/ICCV.2015.333
Other files and links
Link to publication in Scopus