Dynamic textures segmentation with GPU

This work addresses the problem of motion segmentation in video sequences using dynamic textures. Motion can be globally modeled as a statistical visual process know as dynamic texture. Specifically, we use the mixtures of dynamic textures model which can simultaneously handle different visual proce...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Rodríguez, J.M., Gómez Fernández, F., Buemi, M.E., Jacobo-Berlles, J.
Formato:	SER
Materias:	Computer vision applications Cost benefit ratio Dynamic textures GPU implementation GPU programming Motion segmentation Performance analysis Video sequences Visual process Computer vision Image analysis Textures
Acceso en línea:	http://hdl.handle.net/20.500.12110/paper_03029743_v7441LNCS_n_p607_Rodriguez
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	todo:paper_03029743_v7441LNCS_n_p607_Rodriguez
record_format	dspace
spelling	todo:paper_03029743_v7441LNCS_n_p607_Rodriguez2023-10-03T15:19:28Z Dynamic textures segmentation with GPU Rodríguez, J.M. Gómez Fernández, F. Buemi, M.E. Jacobo-Berlles, J. Computer vision applications Cost benefit ratio Dynamic textures GPU implementation GPU programming Motion segmentation Performance analysis Video sequences Visual process Computer vision Image analysis Textures This work addresses the problem of motion segmentation in video sequences using dynamic textures. Motion can be globally modeled as a statistical visual process know as dynamic texture. Specifically, we use the mixtures of dynamic textures model which can simultaneously handle different visual processes. Nowadays, GPU are becoming increasingly popular in computer vision applications because of their cost-benefit ratio. However, GPU programming is not a trivial task and not all algorithms can be easily switched to GPU. In this paper, we made two implementations of a known motion segmentation algorithm based on mixtures of dynamic textures. One using CPU and the other ported to GPU. The performance analyses show the scenarios for which it is worthwhile to do the full GPU implementation of the motion segmentation process. © 2012 Springer-Verlag. Fil:Gómez Fernández, F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Buemi, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Jacobo-Berlles, J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. SER info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03029743_v7441LNCS_n_p607_Rodriguez
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Computer vision applications Cost benefit ratio Dynamic textures GPU implementation GPU programming Motion segmentation Performance analysis Video sequences Visual process Computer vision Image analysis Textures
spellingShingle	Computer vision applications Cost benefit ratio Dynamic textures GPU implementation GPU programming Motion segmentation Performance analysis Video sequences Visual process Computer vision Image analysis Textures Rodríguez, J.M. Gómez Fernández, F. Buemi, M.E. Jacobo-Berlles, J. Dynamic textures segmentation with GPU
topic_facet	Computer vision applications Cost benefit ratio Dynamic textures GPU implementation GPU programming Motion segmentation Performance analysis Video sequences Visual process Computer vision Image analysis Textures
description	This work addresses the problem of motion segmentation in video sequences using dynamic textures. Motion can be globally modeled as a statistical visual process know as dynamic texture. Specifically, we use the mixtures of dynamic textures model which can simultaneously handle different visual processes. Nowadays, GPU are becoming increasingly popular in computer vision applications because of their cost-benefit ratio. However, GPU programming is not a trivial task and not all algorithms can be easily switched to GPU. In this paper, we made two implementations of a known motion segmentation algorithm based on mixtures of dynamic textures. One using CPU and the other ported to GPU. The performance analyses show the scenarios for which it is worthwhile to do the full GPU implementation of the motion segmentation process. © 2012 Springer-Verlag.
format	SER
author	Rodríguez, J.M. Gómez Fernández, F. Buemi, M.E. Jacobo-Berlles, J.
author_facet	Rodríguez, J.M. Gómez Fernández, F. Buemi, M.E. Jacobo-Berlles, J.
author_sort	Rodríguez, J.M.
title	Dynamic textures segmentation with GPU
title_short	Dynamic textures segmentation with GPU
title_full	Dynamic textures segmentation with GPU
title_fullStr	Dynamic textures segmentation with GPU
title_full_unstemmed	Dynamic textures segmentation with GPU
title_sort	dynamic textures segmentation with gpu
url	http://hdl.handle.net/20.500.12110/paper_03029743_v7441LNCS_n_p607_Rodriguez
work_keys_str_mv	AT rodriguezjm dynamictexturessegmentationwithgpu AT gomezfernandezf dynamictexturessegmentationwithgpu AT buemime dynamictexturessegmentationwithgpu AT jacoboberllesj dynamictexturessegmentationwithgpu
_version_	1807322761390981120

Dynamic textures segmentation with GPU

Ejemplares similares