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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Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
2017-10-01
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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 |
_version_ |
1721461988859576320 |