Detection of unseen patches trackable by linear predictors

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00187100" target="_blank" >RIV/68407700:21230/11:00187100 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Detection of unseen patches trackable by linear predictors

Popis výsledku v původním jazyce

Linear predictors (LPs) are being used for tracking because of their computational efficiency which is better than steepest descent methods (e.g. Lucas-Kanade). The only disadvantage of LPs is the necessary learning phase which hinders the predictors applicability as a general patch tracker. We address this limitation and propose to learn a bank of LPs off-line and develop an on-line detector which selects image regions that could be tracked by some predictor from the bank. The proposed detector differssignificantly from the usual solutions that attempt to find the closest match between a candidate patch and a database of exemplars. We construct the detector directly from the learned linear predictor. The detector positively detects the learned patches, but also many other image patches, which were not used in LP learning phase. This means, that the LP is able to track also previously unseen image patches, the appearances of which are often significantly diverse from the patches used.

Název v anglickém jazyce

Detection of unseen patches trackable by linear predictors

Popis výsledku anglicky

Linear predictors (LPs) are being used for tracking because of their computational efficiency which is better than steepest descent methods (e.g. Lucas-Kanade). The only disadvantage of LPs is the necessary learning phase which hinders the predictors applicability as a general patch tracker. We address this limitation and propose to learn a bank of LPs off-line and develop an on-line detector which selects image regions that could be tracked by some predictor from the bank. The proposed detector differssignificantly from the usual solutions that attempt to find the closest match between a candidate patch and a database of exemplars. We construct the detector directly from the learned linear predictor. The detector positively detects the learned patches, but also many other image patches, which were not used in LP learning phase. This means, that the LP is able to track also previously unseen image patches, the appearances of which are often significantly diverse from the patches used.

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

CVWW '11: Proceedings of the 16th Computer Vision Winter Workshop

ISBN

978-3-85125-129-6

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

107-114

Název nakladatele

Graz University of Technology

Místo vydání

Graz

Místo konání akce

Mitterberg

Datum konání akce

2. 2. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—