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Motion features to enhance scene segmentation in active visual attention

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dc.contributor.author Fernández Graciani, Miguel Ángel es_ES
dc.contributor.author Fernández Caballero, Antonio es_ES
dc.contributor.author Delgado García, Ana Esperanza es_ES
dc.contributor.author López Bonal, María Teresa es_ES
dc.contributor.author Mira Mira, José es_ES
dc.date.accessioned 2012-03-21T07:13:07Z
dc.date.available 2012-03-21T07:13:07Z
dc.date.issued 2006 es_ES
dc.identifier.citation Pattern Recognition Letters, 2006, 27(5): 469-478 es_ES
dc.identifier.issn 0167-8655 es_ES
dc.identifier.uri http://hdl.handle.net/10578/2149
dc.description.abstract A new computational model for active visual attention is introduced in this paper. The method extracts motion and shape features from video image sequences, and integrates these features to segment the input scene. The aim of this paper is to highlight the importance of the motion features present in our algorithms in the task of refining and/or enhancing scene segmentation in the method proposed. The estimation of these motion parameters is performed at each pixel of the input image by means of the accumulative computation method, using the so-called permanency memories. The paper shows some examples of how to use the ?motion presence?, ?module of the velocity? and ?angle of the velocity? motion features, all obtained from accumulative computation method, to adjust different scene segmentation outputs in this dynamic visual attention method. es_ES
dc.format text/plain en_US
dc.language.iso es en_US
dc.publisher Elsevier Science es_ES
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Ingenierías es_ES
dc.title Motion features to enhance scene segmentation in active visual attention es_ES
dc.type info:eu-repo/semantics/article en_US

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