dc.contributor | Ohio State Univ | |
dc.contributor | Universidade Federal de São Paulo (UNIFESP) | |
dc.contributor | Universidade de São Paulo (USP) | |
dc.contributor | Chinese Acad Sci | |
dc.creator | Quiles, Marcos G. [UNIFESP] | |
dc.creator | Wang, DeLiang | |
dc.creator | Zhao, Liang | |
dc.creator | Romero, Roseli A. F. | |
dc.creator | Huang, De-Shuang | |
dc.date.accessioned | 2016-01-24T14:05:59Z | |
dc.date.accessioned | 2022-10-07T20:45:32Z | |
dc.date.available | 2016-01-24T14:05:59Z | |
dc.date.available | 2022-10-07T20:45:32Z | |
dc.date.created | 2016-01-24T14:05:59Z | |
dc.date.issued | 2011-01-01 | |
dc.identifier | Neural Networks. Oxford: Pergamon-Elsevier B.V., v. 24, n. 1, p. 54-64, 2011. | |
dc.identifier | 0893-6080 | |
dc.identifier | http://repositorio.unifesp.br/handle/11600/33284 | |
dc.identifier | 10.1016/j.neunet.2010.09.002 | |
dc.identifier | WOS:000289013500006 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/4022422 | |
dc.description.abstract | Attention is a critical mechanism for visual scene analysis. By means of attention, it is possible to break down the analysis of a complex scene to the analysis of its parts through a selection process. Empirical studies demonstrate that attentional selection is conducted on visual objects as a whole. We present a neurocomputational model of object-based selection in the framework of oscillatory correlation. By segmenting an input scene and integrating the segments with their conspicuity obtained from a saliency map, the model selects salient objects rather than salient locations. the proposed system is composed of three modules: a saliency map providing saliency values of image locations, image segmentation for breaking the input scene into a set of objects, and object selection which allows one of the objects of the scene to be selected at a time. This object selection system has been applied to real gray-level and color images and the simulation results show the effectiveness of the system. (C) 2010 Elsevier B.V. All rights reserved. | |
dc.language | eng | |
dc.publisher | Elsevier B.V. | |
dc.relation | Neural Networks | |
dc.rights | http://www.elsevier.com/about/open-access/open-access-policies/article-posting-policy | |
dc.rights | Acesso restrito | |
dc.subject | Object selection | |
dc.subject | LEGION | |
dc.subject | Oscillatory correlation | |
dc.subject | Visual attention | |
dc.title | Selecting salient objects in real scenes: An oscillatory correlation model | |
dc.type | Artigo | |