Title:
Interactive Object Segmentation using Binary Inputs

dc.contributor.author Manivasagam, Sivabalan
dc.contributor.committeeMember Rozell, Christopher
dc.contributor.committeeMember Davenport, Mark
dc.contributor.department Computer Science
dc.date.accessioned 2018-08-20T19:10:49Z
dc.date.available 2018-08-20T19:10:49Z
dc.date.created 2018-05
dc.date.issued 2018-05
dc.date.submitted May 2018
dc.date.updated 2018-08-20T19:10:49Z
dc.description.abstract Every day, humans use their vision to process millions of pixels and select regions of interest. This task of highlighting and grouping pixels of interest in a scene is called image segmentation, and it is a fundamental method that humans use to communicate with each other ideas, concepts, and emotions. We introduce a method derived from feedback information theory that allows individuals with motor control disabilities to perform image segmentation using only binary inputs and a simple encoding scheme. We propose two versions of our algorithm, and evaluate their ability to specify desired regions for the user with restricted inputs and noise on large, publicly available image data sets. We also compare our method to the previous best algorithm, developed by Rupprecht et al.
dc.description.degree Undergraduate
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/60358
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Segmentation
dc.title Interactive Object Segmentation using Binary Inputs
dc.type Text
dc.type.genre Undergraduate Thesis
dspace.entity.type Publication
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Computer Science
local.contributor.corporatename Undergraduate Research Opportunities Program
local.relation.ispartofseries Undergraduate Research Option Theses
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relation.isOrgUnitOfPublication 6b42174a-e0e1-40e3-a581-47bed0470a1e
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relation.isSeriesOfPublication e1a827bd-cf25-4b83-ba24-70848b7036ac
thesis.degree.level Undergraduate
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