Discriminative Correlation Filter Tracker with Channel and Spatial Reliability
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00318711" target="_blank" >RIV/68407700:21230/18:00318711 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s11263-017-1061-3" target="_blank" >https://doi.org/10.1007/s11263-017-1061-3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11263-017-1061-3" target="_blank" >10.1007/s11263-017-1061-3</a>
Alternative languages
Result language
angličtina
Original language name
Discriminative Correlation Filter Tracker with Channel and Spatial Reliability
Original language description
Short-term tracking is an open and challenging problem for which discriminative correlation filters (DCF) have shown excellent performance. We introduce the channel and spatial reliability concepts to DCF tracking and provide a learning algorithm for its efficient and seamless integration in the filter update and the tracking process. The spatial reliability map adjusts the filter support to the part of the object suitable for tracking. This both allows to enlarge the search region and improves tracking of non-rectangular objects. Reliability scores reflect channel-wise quality of the learned filters and are used as feature weighting coefficients in localization. Experimentally, with only two simple standard feature sets, HoGs and colornames, the novel CSR-DCF method---DCF with channel and spatial reliability---achieves state-of-the-art results on VOT 2016, VOT 2015 and OTB100. The CSR-DCF runs close to real-time on a CPU.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
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
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Computer Vision
ISSN
0920-5691
e-ISSN
1573-1405
Volume of the periodical
126
Issue of the periodical within the volume
7
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
18
Pages from-to
671-688
UT code for WoS article
000433072800001
EID of the result in the Scopus database
2-s2.0-85047409502