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Reference TypeConference Paper (Conference Proceedings)
Last Update2002: administrator
Metadata Last Update2020: administrator
Citation KeyNevesBoreGonz:2000:TaSeBo
TitleTarget search by bottom-up and top-down fuzzy information
Access Date2021, Jan. 19
Number of Files1
Size630 KiB
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Author1 Neves, Evelina Maria de Almeida
2 Borelli, Joćo Eduardo
3 Gonzaga, Adilson
EditorCarvalho, Paulo Cezar Pinto
Walter, Marcelo
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 13 (SIBGRAPI)
Conference LocationGramado, RS, Brazil
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
OrganizationSBC - Brazilian Computer Society
History2008-07-17 14:10:49 :: administrator -> banon ::
2008-08-26 15:23:01 :: banon -> administrator ::
2009-08-13 20:36:52 :: administrator -> banon ::
2010-08-28 20:00:08 :: banon -> administrator ::
2020-02-19 02:58:51 :: administrator -> :: 2000
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Is the master or a copy?is the master
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Content TypeExternal Contribution
Keywordsvisual perception, target search, bottom-up fuzzy information, top-down fuzzy information, feature extraction, visual field, human visual attention, fuzzy net, fuzzy subsystems, decision rules, visual perception, Gestalt laws, salience index, geometrical objects.
AbstractOne of the basic tasks assigned to the attentional mechanism is to decide which location in the visual field we must pay attention first. An object containing a distinctive feature can attract attention in a bottom-up way. By comparing one object with the others present in the scene, bottom-up conspicuity features are used to guide attention to the most different object. Top-down hints are based on the previous knowledge about the objects or on which features are important to locate them and also have a large influence on the attended locations. Inspired by the mechanisms of human visual attention we developed a new methodology to integrate bottom-up and top-down information by using a fuzzy net containing three fuzzy subsystems. The first bottom-up subsystem allow us to combine features and infer with great flexibility some intuitive decision rules based on the visual perception principles such as the Gestalt laws. The second top-down subsystem combines different features according to the relevance of them in different tasks. Finally, the last subsystem integrates the information of the previous systems and gives a general salience index. The new methodology was tested in geometrical objects considering the features that attract attention to human beings.
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NotesThe conference was held in Gramado, RS, Brazil, from October 17 to 20.
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