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Towards a Smart Selection of Hybrid Platforms for Multimedia Processing

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemases
dc.contributor.authorMahmoudi, Sidi Ahmed
dc.contributor.authorManneback, Pierre
dc.contributor.editorCarretero Pérez, Jesús
dc.contributor.editorGarcía Blas, Javier
dc.contributor.editorPetcu, Dana
dc.date.accessioned2016-04-29T09:56:47Z
dc.date.available2016-04-29T09:56:47Z
dc.date.issued2016-02
dc.descriptionProceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016.en
dc.description.abstractNowadays, images and videos have been present everywhere, they can come directly from camera, mobile devices or from other peoples that share their images and videos. The latter are used to illustrate different objects in a large number of situations. This makes from image and video processing algorithms a very important tool used for various domains related to computer vision such as video surveillance, medical imaging and database (images and videos) indexation methods. The performance of these algorithms have been so reduced due the the high intensive computation required when using new image and video standards. In this paper, we propose a new framework that allows users to select in a smart and efficient way the processing units (GPU or/and CPU) within heterogeneous systems, when treating different kinds of multimedia objects : single image, multiple images, multiple videos and video in real time. The framework disposes of different image and video primitive functions that are implemented on GPU, such as shape (silhouette) detection, motion tracking using optical flow estimation, edges and corners detection. We have exploited these functions for several situations such as indexing videos, segmenting vertebrae in in X-ray and MR images, detecting and localizing event in multi-user scenarios. Experimentation showed interesting accelerations ranging from 6 to 118, by comparison with sequential implementations. Moreover, the parallel and heterogeneous implementations offered lower power consumption as a result for the fast treatment.en
dc.description.sponsorshipEuropean Cooperation in Science and Technology. COSTen
dc.format.extent4
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationCarretero Pérez, Jesús; et.al. (eds.). (2016). Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016). Timisoara, Romania. Universidad Carlos III de Madrid, ARCOS. Pp. 5-8.en
dc.identifier.isbn978-84-608-6309-0
dc.identifier.publicationfirstpage5
dc.identifier.publicationlastpage8
dc.identifier.publicationtitleProceedings of the First PhD Symposium on Sustainable UltrascaleComputing Systems (NESUS PhD 2016)en
dc.identifier.urihttps://hdl.handle.net/10016/22881
dc.language.isoeng
dc.relation.eventdateFebruary 8-11, 2016en
dc.relation.eventnumber1
dc.relation.eventplaceTimisoara, Romaniaen
dc.relation.eventtitlePhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otherGPUen
dc.subject.otherHeterogeneous architecturesen
dc.subject.otherImage and video processingen
dc.subject.otherMedical imagingen
dc.subject.otherMotion trackingen
dc.titleTowards a Smart Selection of Hybrid Platforms for Multimedia Processingen
dc.typeconference paper*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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