Fluid Motion Recovery by Coupling Dense and Parametric Vector Fields

In this paper we address the problem of estimating and analyzing the motion in image sequences that involve fluid phenomena. In this context standard motion estimation techniques are not well adapted and more dedicated approaches have to be designed. In this prospect, we propose to estimate in a joint and cooperative way a dense motion field and a peculiar parametric representation of the flow. The parametric model issues from an extension of Rankine vortex model and includes a laminar flow field. Dense and parametric fields are estimated by minimizing a robust global objective function thanks to a specific alternate scheme. The method has been validated on different kinds of meteorological image sequences. 1 Background: Fluid Motion Estimation In a number of domains, image sequences that involve fluid phenomena, have to be analyzed: In environmental sciences (oceanography, meteorology, climatology, etc.), ocean and atmosphere evolutions are observed via satellite sensors [5, 9]; In m...

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: Étienne Mémin, Patrick Pérez
• Keywords: Computer Vision, Fluid Motion Estimation, ICCV 1999, Image Sequences, Imaged Fluid Phenomena, Involve Fluid Phenomena, Motion Estimation Techniques