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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F11%3A00187104%21RIV12-MSM-21230___
rdf:type
skos:Concept n18:Vysledek
dcterms: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, called the 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 based on 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. 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, called the 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 based on 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.
dcterms:title
Robustifying the Flock of Trackers Robustifying the Flock of Trackers
skos:prefLabel
Robustifying the Flock of Trackers Robustifying the Flock of Trackers
skos:notation
RIV/68407700:21230/11:00187104!RIV12-MSM-21230___
n18:predkladatel
n19:orjk%3A21230
n3:aktivita
n10:P n10:Z
n3:aktivity
P(GAP103/10/1585), Z(MSM6840770038)
n3:dodaniDat
n11:2012
n3:domaciTvurceVysledku
n4:1711326 n4:2511169
n3:druhVysledku
n8:D
n3:duvernostUdaju
n16:S
n3:entitaPredkladatele
n21:predkladatel
n3:idSjednocenehoVysledku
227307
n3:idVysledku
RIV/68407700:21230/11:00187104
n3:jazykVysledku
n5:eng
n3:klicovaSlova
computer vision; tracking
n3:klicoveSlovo
n7:tracking n7:computer%20vision
n3:kontrolniKodProRIV
[F62A1B9D8697]
n3:mistoKonaniAkce
Mitterberg
n3:mistoVydani
Graz
n3:nazevZdroje
CVWW '11: Proceedings of the 16th Computer Vision Winter Workshop
n3:obor
n12:JD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n13:GAP103%2F10%2F1585
n3:rokUplatneniVysledku
n11:2011
n3:tvurceVysledku
Matas, Jiří Vojíř, Tomáš
n3:typAkce
n17:WRD
n3:zahajeniAkce
2011-02-02+01:00
n3:zamer
n23:MSM6840770038
s:numberOfPages
7
n14:hasPublisher
Graz University of Technology
n22:isbn
978-3-85125-129-6
n15:organizacniJednotka
21230