Skip to Main content Skip to Navigation
New interface
Conference papers

Divergence-Free Motion Estimation

Abstract : This paper describes an innovative approach to estimate motion from image observations of divergence-free flows. Unlike most state-of-the-art methods, which only minimize the divergence of the motion field, our approach utilizes the vorticity-velocity formalism in order to construct a motion field in the subspace of divergence free functions. A 4DVAR-like image assimilation method is used to generate an estimate of the vorticity field given image observations. Given that vorticity estimate, the motion is obtained solving the Poisson equation. Results are illustrated on synthetic image observations and compared to those obtained with state-of-the-art methods, in order to quantify the improvements brought by the presented approach. The method is then applied to ocean satellite data to demonstrate its performance on the real images.
Document type :
Conference papers
Complete list of metadata

Cited literature [26 references]  Display  Hide  Download
Contributor : Nathalie Gaudechoux Connect in order to contact the contributor
Submitted on : Friday, November 15, 2013 - 5:07:06 PM
Last modification on : Friday, November 18, 2022 - 9:26:52 AM
Long-term archiving on: : Sunday, February 16, 2014 - 2:40:21 AM


Files produced by the author(s)



Isabelle Herlin, Dominique Béréziat, Nicolas Mercier, Sergiy Zhuk. Divergence-Free Motion Estimation. ECCV 2012 - European Conference on Computer Vision, Oct 2012, Florence, Italy. pp.15-27, ⟨10.1007/978-3-642-33765-9_2⟩. ⟨hal-00742021⟩



Record views


Files downloads