Linear Predictors for Fast Simultaneous Modeling and Tracking
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F07%3A03142470" target="_blank" >RIV/68407700:21230/07:03142470 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Linear Predictors for Fast Simultaneous Modeling and Tracking
Original language description
An approach for fast tracking of arbitrary image features with no prior model and no offline learning stage is presented. Fast tracking is achieved using banks of linear displacement predictors learnt online. A multi-modal appearance model is also learnton-the-fly that facilitates the selection of subsets of predictors suitable for prediction in the next frame. The approach is demonstrated in real-time on a number of challenging video sequences and experimentally compared to other simultaneous modelingand tracking approaches with favourable results.
Czech name
Linear Predictors for Fast Simultaneous Modeling and Tracking
Czech description
An approach for fast tracking of arbitrary image features with no prior model and no offline learning stage is presented. Fast tracking is achieved using banks of linear displacement predictors learnt online. A multi-modal appearance model is also learnton-the-fly that facilitates the selection of subsets of predictors suitable for prediction in the next frame. The approach is demonstrated in real-time on a number of challenging video sequences and experimentally compared to other simultaneous modelingand tracking approaches with favourable results.
Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/1M0567" target="_blank" >1M0567: Centre for Applied Cybernetics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2007
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
NRTL 2007: Proceedings of workshop on Non-rigid registration and tracking through learning - ICCV
ISBN
978-1-4244-1630-1
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
Omnipress
Place of publication
Madison
Event location
Rio de Janeiro
Event date
Oct 14, 2007
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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