Optimal Orthogonal Basis and Image Assimilation: Motion Modeling - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2013

Optimal Orthogonal Basis and Image Assimilation: Motion Modeling

Abstract

This paper describes modeling and numerical computation of orthogonal bases, which are used to describe images and motion fields. Motion estimation from image data is then studied on subspaces spanned by these bases. A reduced model is obtained as the Galerkin projection on these subspaces of a physical model, based on Euler and optical flow equations. A data assimilation method is studied, which assimilates coefficients of image data in the reduced model in order to estimate motion coefficients. The approach is first quantified on synthetic data: it demonstrates the interest of model reduction as a compromise between results quality and computational cost. Results obtained on real data are then displayed so as to illustrate the method.
Fichier principal
Vignette du fichier
ICCV-2013.pdf (1.93 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00871330 , version 1 (31-10-2013)

Identifiers

  • HAL Id : hal-00871330 , version 1

Cite

Etienne Huot, Isabelle Herlin, Giuseppe Papari. Optimal Orthogonal Basis and Image Assimilation: Motion Modeling. ICCV - International Conference on Computer Vision, Dec 2013, Sydney, Australia. ⟨hal-00871330⟩
186 View
229 Download

Share

Gmail Facebook X LinkedIn More