Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICARCV.2012.6485322
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dc.titleA color grouping method for detection of object regions based on local saliency
dc.contributor.authorJiayun, W.
dc.contributor.authorBin, L.K.
dc.date.accessioned2014-06-19T05:30:06Z
dc.date.available2014-06-19T05:30:06Z
dc.date.issued2012
dc.identifier.citationJiayun, W.,Bin, L.K. (2012). A color grouping method for detection of object regions based on local saliency. 2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012 : 1165-1169. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICARCV.2012.6485322" target="_blank">https://doi.org/10.1109/ICARCV.2012.6485322</a>
dc.identifier.isbn9781467318716
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/73008
dc.description.abstractThe detection of object regions based on local saliency has been with great interest in computer vision for its potential contributions to applications, such as recognition, because objects of interest could be contained in salient regions. However, regions are extracted from local salient locations by simple procedures without the global inference, resulting in poor segmentation of possible objects. In this paper, a two-strategy has been proposed to introduce local saliency into foreground subtraction, a color grouping method. By using only color information and no prior higher level knowledge about objects and scenes, multiple foreground regions are extracted simultaneously according to visual attention based salient locations. The prominence score is defined to further evaluate these regions for their possibility to contain objects of interest. © 2012 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICARCV.2012.6485322
dc.sourceScopus
dc.subjectcolor grouping
dc.subjectsaliency
dc.subjectsegmentation
dc.typeConference Paper
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1109/ICARCV.2012.6485322
dc.description.sourcetitle2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012
dc.description.page1165-1169
dc.identifier.isiutNOT_IN_WOS
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