Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/54504
Título: | A new energy-based method for 3D motion estimation of incompressible PIV flows | Autores/as: | Alvarez, L. Castaño, C. A. García, M. Krissian, K. Mazorra, L. Salgado, A. Sánchez, J. |
Clasificación UNESCO: | 220990 Tratamiento digital. Imágenes 120601 Construcción de algoritmos 120602 Ecuaciones diferenciales 120304 Inteligencia artificial |
Palabras clave: | Optical-Flow Variational Approach Fluid-Flows Computation Velocimetry, et al. |
Fecha de publicación: | 2009 | Editor/a: | 1077-3142 | Publicación seriada: | Computer Vision and Image Understanding | Resumen: | 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. | URI: | http://hdl.handle.net/10553/54504 | ISSN: | 1077-3142 | DOI: | 10.1016/j.cviu.2009.01.005 | Fuente: | Computer Vision and Image Understanding[ISSN 1077-3142],v. 113, p. 802-810 |
Colección: | Artículos |
Citas SCOPUSTM
15
actualizado el 15-dic-2024
Citas de WEB OF SCIENCETM
Citations
14
actualizado el 15-dic-2024
Visitas
85
actualizado el 09-mar-2024
Google ScholarTM
Verifica
Altmetric
Comparte
Exporta metadatos
Los elementos en ULPGC accedaCRIS están protegidos por derechos de autor con todos los derechos reservados, a menos que se indique lo contrario.