In this paper we propose a new motion estimator for image sequences depicting fluid flows. The proposed estimator is based on the Helmholtz decomposition of vector fields. This decomposition consists in representing the velocity field as a sum of a divergence free component and a curl free component. The objective is to provide a low-dimensional parametric representation of optical flows by depicting them as a flow generated by a small number of vortex and source particles. Both components are approximated using a discretization of the vorticity and divergence maps through regularized Dirac measures. The resulting so called irrotational and solenoidal fields consist then in linear combinations of basis functions obtained through a convolution product of the Green kernel gradient and the vorticity map or the divergence map respectively. The coefficient values and the basis function parameters are obtained by minimization of a functional relying on an integrated version of mass conservation principle of fluid mechanics. Results are provided on real world sequences. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Cuzol, A., & Mémin, E. (2005). Vortex and source particles for fluid motion estimation. In Lecture Notes in Computer Science (Vol. 3459, pp. 254–266). Springer Verlag. https://doi.org/10.1007/11408031_22
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