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Title: Bio-inspired Boosting for Moving Objects Segmentation
Authors: Martins,I
Pedro Miguel Carvalho
Luís Corte Real
Luis Alba Castro,JL
Issue Date: 2016
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.
metadata.dc.type: conferenceObject
Appears in Collections:CTM - Articles in International Conferences

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