Adaptive Visual Tracking with Minimum Uncertainty Gap Estimation

A novel tracking algorithm is proposed, which robustly tracks a target by finding the state that minimizes the likelihood uncertainty. Likelihood uncertainty is estimated by determining the gap between the lower and upper bounds of likelihood. By minimizing the gap between the two bounds, the propos...

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Détails bibliographiques
Publié dans:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 39(2017), 1 vom: 05. Jan., Seite 18-31
Auteur principal: Kwon, Junseok (Auteur)
Autres auteurs: Lee, Kyoung Mu
Format: Article en ligne
Langue:English
Publié: 2017
Accès à la collection:IEEE transactions on pattern analysis and machine intelligence
Sujets:Journal Article