Bio-inspired Boosting for Moving Objects Segmentation

dc.contributor.author Martins,I en
dc.contributor.author Pedro Miguel Carvalho en
dc.contributor.author Luís Corte Real en
dc.contributor.author Luis Alba Castro,JL en
dc.date.accessioned 2018-01-05T13:32:05Z
dc.date.available 2018-01-05T13:32:05Z
dc.date.issued 2016 en
dc.description.abstract Developing robust and universal methods for unsupervised segmentation of moving objects in video sequences has proved to be a hard and challenging task. State-of-the-art methods show good performance in a wide range of situations, but systematically fail when facing more challenging scenarios. Lately, a number of image processing modules inspired in biological models of the human visual system have been explored in different areas of application. This paper proposes a bio-inspired boosting method to address the problem of unsupervised segmentation of moving objects in video that shows the ability to overcome some of the limitations of widely used state-of-the-art methods. An exhaustive set of experiments was conducted and a detailed analysis of the results, using different metrics, revealed that this boosting is more significant when challenging scenarios are faced and state-of-the-art methods tend to fail. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/5519
dc.identifier.uri http://dx.doi.org/10.1007/978-3-319-41501-7_45 en
dc.language eng en
dc.relation 243 en
dc.relation 4358 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Bio-inspired Boosting for Moving Objects Segmentation en
dc.type conferenceObject en
dc.type Publication en
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