Please use this identifier to cite or link to this item:
Title: A new energy-based method for 3D motion estimation of incompressible PIV flows
Authors: Alvarez, L. 
Castaño, C. A.
García, M.
Krissian, K.
Mazorra, L. 
Salgado, A.
Sánchez, J. 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120304 Inteligencia artificial
Keywords: Optical-Flow
Variational Approach
Velocimetry, et al
Issue Date: 2009
Publisher: 1077-3142
Journal: Computer Vision and Image Understanding 
Abstract: Motion estimation has many applications in fluid analysis, and a lot of work has been carried Out using Particle Image Velocimetry (PIV) to capture and measure the flow motion from sequences of 2D images. Recent technological advances allow capturing 3D PIV sequences of moving particles. In the context of 3D flow motion, the assumption of incompressibility is an important physical property that is satisfied by a large class of problems and experiments. Standard motion estimation techniques in computer vision do not take into account the physical constraints of the flow, which is a very interesting and challenging problem. In this paper, we Propose a new variational motion estimation technique which includes the incompressibility of the flow as a Constraint to the minimization problem. We analyze, from a theoretical point of view, the influence of this constraint and we design a new numerical algorithm for motion estimation which enforces it. The performance of the proposed technique is evaluated from numerical experiments on synthetic and real data. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.
ISSN: 1077-3142
DOI: 10.1016/j.cviu.2009.01.005
Source: Computer Vision and Image Understanding[ISSN 1077-3142],v. 113, p. 802-810
Appears in Collections:Artículos
Show full item record


checked on Jul 14, 2024


checked on Jul 14, 2024

Page view(s)

checked on Mar 9, 2024

Google ScholarTM




Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.