Baseline and triangulation geometry in a standard plenoptic camera

2.50
Hdl Handle:
http://hdl.handle.net/10547/622229
Title:
Baseline and triangulation geometry in a standard plenoptic camera
Authors:
Hahne, Christopher ( 0000-0003-2786-9905 ) ; Aggoun, Amar; Velisavljević, Vladan ( 0000-0001-9980-9368 ) ; Fiebig, Susanne; Pesch, Matthias
Abstract:
In this paper, we demonstrate light field triangulation to determine depth distances and baselines in a plenoptic camera. The advancement of micro lenses and image sensors enabled plenoptic cameras to capture a scene from different viewpoints with sufficient spatial resolution. While object distances can be inferred from disparities in a stereo viewpoint pair using triangulation, this concept remains ambiguous when applied in case of plenoptic cameras. We present a geometrical light field model allowing the triangulation to be applied to a plenoptic camera in order to predict object distances or to specify baselines as desired. It is shown that distance estimates from our novel method match those of real objects placed in front of the camera. Additional benchmark tests with an optical design software further validate the model’s accuracy with deviations of less than 0:33 % for several main lens types and focus settings. A variety of applications in the automotive and robotics field can benefit from this estimation model.
Citation:
Hahne C., Aggoun A., Velisavljevic V., Fiebig S., Pesch M. (2017) 'Baseline and triangulation geometry in a standard plenoptic camera', International Journal of Computer Vision 126 (1) 21-35
Publisher:
Springer
Journal:
International Journal of Computer Vision
Issue Date:
22-Sep-2017
URI:
http://hdl.handle.net/10547/622229
DOI:
10.1007/s11263-017-1036-4
Additional Links:
https://link.springer.com/article/10.1007/s11263-017-1036-4
Type:
Article
Language:
en
ISSN:
0920-5691
EISSN:
1573-1405
Appears in Collections:
Engineering

Full metadata record

DC FieldValue Language
dc.contributor.authorHahne, Christopheren
dc.contributor.authorAggoun, Amaren
dc.contributor.authorVelisavljević, Vladanen
dc.contributor.authorFiebig, Susanneen
dc.contributor.authorPesch, Matthiasen
dc.date.accessioned2017-09-25T11:38:41Z-
dc.date.available2017-09-25T11:38:41Z-
dc.date.issued2017-09-22-
dc.identifier.citationHahne C., Aggoun A., Velisavljevic V., Fiebig S., Pesch M. (2017) 'Baseline and triangulation geometry in a standard plenoptic camera', International Journal of Computer Vision 126 (1) 21-35en
dc.identifier.issn0920-5691-
dc.identifier.doi10.1007/s11263-017-1036-4-
dc.identifier.urihttp://hdl.handle.net/10547/622229-
dc.description.abstractIn this paper, we demonstrate light field triangulation to determine depth distances and baselines in a plenoptic camera. The advancement of micro lenses and image sensors enabled plenoptic cameras to capture a scene from different viewpoints with sufficient spatial resolution. While object distances can be inferred from disparities in a stereo viewpoint pair using triangulation, this concept remains ambiguous when applied in case of plenoptic cameras. We present a geometrical light field model allowing the triangulation to be applied to a plenoptic camera in order to predict object distances or to specify baselines as desired. It is shown that distance estimates from our novel method match those of real objects placed in front of the camera. Additional benchmark tests with an optical design software further validate the model’s accuracy with deviations of less than 0:33 % for several main lens types and focus settings. A variety of applications in the automotive and robotics field can benefit from this estimation model.en
dc.language.isoenen
dc.publisherSpringeren
dc.relation.urlhttps://link.springer.com/article/10.1007/s11263-017-1036-4en
dc.rightsGreen - can archive pre-print and post-print or publisher's version/PDF-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectplenoptic cameraen
dc.titleBaseline and triangulation geometry in a standard plenoptic cameraen
dc.typeArticleen
dc.identifier.eissn1573-1405-
dc.identifier.journalInternational Journal of Computer Visionen
dc.date.updated2017-09-25T11:16:43Z-
dc.description.noteOPEN ACCESS-
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