Long-Term Tracking Through Failure Cases
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00212570" target="_blank" >RIV/68407700:21230/13:00212570 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICCVW.2013.26" target="_blank" >http://dx.doi.org/10.1109/ICCVW.2013.26</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCVW.2013.26" target="_blank" >10.1109/ICCVW.2013.26</a>
Alternative languages
Result language
angličtina
Original language name
Long-Term Tracking Through Failure Cases
Original language description
Long term tracking of an object, given only a single instance in an initial frame, remains an open problem. We propose a visual tracking algorithm, robust to many of the difficulties which often occur in real-world scenes. Correspondences of edge-based features are used, to overcome the reliance on the texture of the tracked object and improve invariance to lighting. Furthermore we address long-term stability, enabling the tracker to recover from drift and to provide redetection following object disappearance or occlusion. The two-module principle is similar to the successful state-of-the-art long-term TLD tracker, however our approach extends to cases of low-textured objects. Besides reporting our results on the VOT Challenge dataset, we perform two additional experiments. Firstly, results on short-term sequences show the performance of tracking challenging objects which represent failure cases for competing state-of-the-art approaches. Secondly, long sequences are tracked, including
Czech name
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Czech description
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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/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
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2013 IEEE International Conference on Computer Vision (ICCV 2013) Worskhops
ISBN
978-0-7695-5161-6
ISSN
1550-5499
e-ISSN
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Number of pages
8
Pages from-to
153-160
Publisher name
IEEE
Place of publication
Piscataway
Event location
Sydney
Event date
Dec 2, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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