Background Subtraction for Time of Flight Imaging

A time of flight camera provides two types of images simultaneously, depth and intensity. In this paper a computational method for background subtraction, combining both images or fast sequences of images, is proposed. The background model is based on unbalanced or semi-supervised classifiers, in pa...

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Main Authors: Javier Giacomantone, María Lucía Violini, Luciano Lorenti
Format: Article
Language:English
Published: Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2017-10-01
Series:Journal of Computer Science and Technology
Subjects:
Online Access:https://journal.info.unlp.edu.ar/JCST/article/view/438
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spelling doaj-4a212183054c47b284de76e9e0ffebfd2021-05-05T13:25:40ZengPostgraduate Office, School of Computer Science, Universidad Nacional de La PlataJournal of Computer Science and Technology1666-60461666-60382017-10-011702e18e1810.24215/16666038.17.e18219Background Subtraction for Time of Flight ImagingJavier Giacomantone0María Lucía Violini1Luciano Lorenti2Institute of Research in Computer Science - School of Computer Science - University of La Plata, ArgentinaInstitute of Research in Computer Science - School of Computer Science - University of La Plata, ArgentinaInstitute of Research in Computer Science - School of Computer Science - University of La Plata, ArgentinaA time of flight camera provides two types of images simultaneously, depth and intensity. In this paper a computational method for background subtraction, combining both images or fast sequences of images, is proposed. The background model is based on unbalanced or semi-supervised classifiers, in particular support vector machines. A brief review of one class support vector machines is first given. A method that combines the range and intensity data in two operational modes is then provided. Finally, experimental results are presented and discussed.https://journal.info.unlp.edu.ar/JCST/article/view/438industrial tof camerasmachine visionpattern recognitionsupport vector machines
collection DOAJ
language English
format Article
sources DOAJ
author Javier Giacomantone
María Lucía Violini
Luciano Lorenti
spellingShingle Javier Giacomantone
María Lucía Violini
Luciano Lorenti
Background Subtraction for Time of Flight Imaging
Journal of Computer Science and Technology
industrial tof cameras
machine vision
pattern recognition
support vector machines
author_facet Javier Giacomantone
María Lucía Violini
Luciano Lorenti
author_sort Javier Giacomantone
title Background Subtraction for Time of Flight Imaging
title_short Background Subtraction for Time of Flight Imaging
title_full Background Subtraction for Time of Flight Imaging
title_fullStr Background Subtraction for Time of Flight Imaging
title_full_unstemmed Background Subtraction for Time of Flight Imaging
title_sort background subtraction for time of flight imaging
publisher Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
series Journal of Computer Science and Technology
issn 1666-6046
1666-6038
publishDate 2017-10-01
description A time of flight camera provides two types of images simultaneously, depth and intensity. In this paper a computational method for background subtraction, combining both images or fast sequences of images, is proposed. The background model is based on unbalanced or semi-supervised classifiers, in particular support vector machines. A brief review of one class support vector machines is first given. A method that combines the range and intensity data in two operational modes is then provided. Finally, experimental results are presented and discussed.
topic industrial tof cameras
machine vision
pattern recognition
support vector machines
url https://journal.info.unlp.edu.ar/JCST/article/view/438
work_keys_str_mv AT javiergiacomantone backgroundsubtractionfortimeofflightimaging
AT marialuciaviolini backgroundsubtractionfortimeofflightimaging
AT lucianolorenti backgroundsubtractionfortimeofflightimaging
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