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  • 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. (en)
Title
  • Robustifying the Flock of Trackers
  • Robustifying the Flock of Trackers (en)
skos:prefLabel
  • Robustifying the Flock of Trackers
  • Robustifying the Flock of Trackers (en)
skos:notation
  • RIV/68407700:21230/11:00187104!RIV12-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GAP103/10/1585), Z(MSM6840770038)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 227307
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/11:00187104
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • computer vision; tracking (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [F62A1B9D8697]
http://linked.open...v/mistoKonaniAkce
  • Mitterberg
http://linked.open...i/riv/mistoVydani
  • Graz
http://linked.open...i/riv/nazevZdroje
  • CVWW '11: Proceedings of the 16th Computer Vision Winter Workshop
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Matas, Jiří
  • Vojíř, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Graz University of Technology
https://schema.org/isbn
  • 978-3-85125-129-6
http://localhost/t...ganizacniJednotka
  • 21230
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