On the Usage of the Trifocal Tensor in Motion Segmentation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F20%3A00347767" target="_blank" >RIV/68407700:21730/20:00347767 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-58565-5_31" target="_blank" >https://doi.org/10.1007/978-3-030-58565-5_31</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-58565-5_31" target="_blank" >10.1007/978-3-030-58565-5_31</a>
Alternative languages
Result language
angličtina
Original language name
On the Usage of the Trifocal Tensor in Motion Segmentation
Original language description
Motion segmentation, i.e., the problem of clustering data in multiple images based on different 3D motions, is an important task for reconstructing and understanding dynamic scenes. In this paper we address motion segmentation in multiple images by combining partial results coming from triplets of images, which are obtained by fitting a number of trifocal tensors to correspondences. We exploit the fact that the trifocal tensor is a stronger model than the fundamental matrix, as it provides fewer but more reliable matches over three images than fundamental matrices provide over the two. We also consider an alternative solution which merges partial results coming from both triplets and pairs of images, showing the strength of three-frame segmentation in a combination with two-frame segmentation. Our real experiments on standard as well as new datasets demonstrate the superior accuracy of the proposed approaches when compared to previous techniques.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computer Vision - ECCV 2020, Part XX
ISBN
978-3-030-58564-8
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
17
Pages from-to
514-530
Publisher name
Springer
Place of publication
Cham
Event location
Glasgow
Event date
Aug 23, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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