Increasing Robustness of the Flock of Trackers

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00200611" target="_blank" >RIV/68407700:21230/12:00200611 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Increasing Robustness of the Flock of Trackers

Popis výsledku v původním jazyce

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 a subset of predicted 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 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 normalized cross-correlation (NCC) predictor are more powerful and almost two times faster than the predictor based on normalized cross-correlation (NCC) and forward-backward procedure (FB). The resulting tracker equipped with the new predictors combined with the normalized cross-correlation p

Název v anglickém jazyce

Increasing Robustness of the Flock of Trackers

Popis výsledku anglicky

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 a subset of predicted 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 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 normalized cross-correlation (NCC) predictor are more powerful and almost two times faster than the predictor based on normalized cross-correlation (NCC) and forward-backward procedure (FB). The resulting tracker equipped with the new predictors combined with the normalized cross-correlation p

Druh

O - Ostatní výsledky

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Centrum pro multi-modální interpretaci dat velkého rozsahu</a><br>

Návaznosti

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

Rok uplatnění

2012

Kód důvěrnosti údajů

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