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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • 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