Robustifying the Flock of Trackers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00187104" target="_blank" >RIV/68407700:21230/11:00187104 - 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
Robustifying the Flock of Trackers
Original language description
The paper presents contributions to the design of the Flock of Trackers (FoT). The FoT trackers estimate the pose of the tracked object by robustly combining displacement estimates from local trackers that cover the object. The first contribution, calledthe Cell FoT, allows local trackers to drift to points good to track. The Cell FoT was compared with the Kalal et al. Grid FoT [4] and outperformed it on all sequences but one and for all local failure prediction methods. As a second contribution, we introduce two new predictors of local tracker failure - the neighbourhood consistency predictor (Nh) and the Markov predictor (Mp) and show that the new predictors combined with the NCC predictor are more powerful than the Kalal et al. [4] predictor basedon NCC and FB. The resulting tracker equipped with the new predictors combined with the NCC predictor was compared with state-of-the-art tracking algorithms and surpassed them in terms of the number of sequences where a given tracking.
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/GAP103%2F10%2F1585" target="_blank" >GAP103/10/1585: Advanced predictors for object detection and tracking in video</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CVWW '11: Proceedings of the 16th Computer Vision Winter Workshop
ISBN
978-3-85125-129-6
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
91-97
Publisher name
Graz University of Technology
Place of publication
Graz
Event location
Mitterberg
Event date
Feb 2, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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