Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/74021
Título: Optic flow estimation in fluid images I
Autores/as: Alemán Flores, Miguel 
Álvarez, L 
Gonzalez, E. 
Mazorra, L. 
Sánchez, J. 
Clasificación UNESCO: 220990 Tratamiento digital. Imágenes
120304 Inteligencia artificial
120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
120326 Simulación
Fecha de publicación: 2005
Proyectos: Fluid Image Analysis And Description 
Publicación seriada: Cuadernos del Instituto Universitario de Ciencias y Tecnologías Cibernéticas 
Resumen: In this work we present some comparative qualitative results of optic flow estimation in PIV and satellite fluid image sequence. This work has been done in the context of the FLUID Specific Targeted Research project - Contract No 513633 founded by the CEE. The main goal of this paper is to compare in a very basic way 3 optic flow estimation methods in the context of some fluid image sequence provided to us by AEROBIO-CEMAGREF and the ”Laboratorire de M´et´orologie Dynamique de la Ecole Polytechnique” both partners of the FLUID project. In order to simplify the comparison and better understand the comparison results we have used just 2 images of each sequence, so no temporal smoothing or another 3D preprocessing have been performed. We have also implemented ourself in C language the 3 optic flow methods in order to better understand each method and to be sure about what are we doing. The organization of the paper is as follows: In section 1, we describe the optic flow methods we use for comparison purposes. In section 2 we present an invariant analysis of the methods. In section 3, we present the numerical experiments and finally in section 4 we present some conclusions and future works.
URI: http://hdl.handle.net/10553/74021
ISSN: 1575-6807
Fuente: Cuadernos del Instituto Universitario de Ciencias y Tecnologías Cibernéticas [ISSN 1575-6807], n. 0031, p. 1-25
Colección:Artículos
miniatura
PDF
Adobe PDF (19,36 MB)
Vista completa

Visitas

95
actualizado el 13-sep-2024

Descargas

62
actualizado el 13-sep-2024

Google ScholarTM

Verifica


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.