Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00337158" target="_blank" >RIV/68407700:21230/19:00337158 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8953557/keywords#keywords" target="_blank" >https://ieeexplore.ieee.org/document/8953557/keywords#keywords</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2019.00143" target="_blank" >10.1109/CVPR.2019.00143</a>
Alternative languages
Result language
angličtina
Original language name
Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters
Original language description
Standard RGB-D trackers treat the target as a 2D structure, which makes modelling appearance changes related even to out-of-plane rotation challenging. This limitation is addressed by the proposed long-term RGB-D tracker called OTR – Object Tracking by Reconstruction. OTR performs online 3D target reconstruction to facilitate robust learning of a set of view-specific discriminative correlation filters (DCFs). The 3D reconstruction supports two performance- enhancing features: (i) generation of an accurate spatial support for constrained DCF learning from its 2D projection and (ii) point-cloud based estimation of 3D pose change for selection and storage of view-specific DCFs which robustly localize the target after out-of-view rotation or heavy occlusion. Extensive evaluation on the Princeton RGB-D tracking and STC Benchmarks shows OTR outperforms the state-of-the-art by a large margin.
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
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CVPR 2019: Proceedings of the 2019 IEEE Conference on Computer Vision and Pattern Recognition
ISBN
978-1-7281-3293-8
ISSN
1063-6919
e-ISSN
2575-7075
Number of pages
10
Pages from-to
1339-1348
Publisher name
IEEE
Place of publication
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Event location
Long Beach
Event date
Jun 15, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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