Motion Segmentation with Pairwise Matches and Unknown Number of Motions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F21%3A00355881" target="_blank" >RIV/68407700:21730/21:00355881 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICPR48806.2021.9413142" target="_blank" >https://doi.org/10.1109/ICPR48806.2021.9413142</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICPR48806.2021.9413142" target="_blank" >10.1109/ICPR48806.2021.9413142</a>
Alternative languages
Result language
angličtina
Original language name
Motion Segmentation with Pairwise Matches and Unknown Number of Motions
Original language description
In this paper we address motion segmentation, that is the problem of clustering points in multiple images according to a number of moving objects. Two-frame correspondences are assumed as input without prior knowledge about trajectories. Our method is based on principles from “multi-model fitting” and “permutation synchronization”, and - differently from previous techniques working under the same assumptions - it can handle an unknown number of motions. The proposed approach is validated on standard datasets, showing that it can correctly estimate the number of motions while maintaining comparable or better accuracy than the state of the art.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
<a href="/en/project/EF15_003%2F0000468" target="_blank" >EF15_003/0000468: Intelligent Machine Perception</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2020 25th International Conference on Pattern Recognition (ICPR)
ISBN
978-1-7281-8809-6
ISSN
1051-4651
e-ISSN
1051-4651
Number of pages
8
Pages from-to
2896-2903
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
Milan
Event date
Jan 10, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000678409203002