Visual tracking using interactive factorial hidden Markov models

Autor: Jin Wook Paeng, Junseok Kwon
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IET Signal Processing, Vol 15, Iss 6, Pp 365-374 (2021)
Druh dokumentu: article
ISSN: 1751-9683
1751-9675
DOI: 10.1049/sil2.12037
Popis: Abstract The authors present a novel tracking algorithm based on a factorial hidden Markov model (FHMM) that can utilise the structured information of a target. An FHMM consists of multiple hidden Markov models (HMMs), wherein each HMM aims to represent a different part of the target. Then, the geometric relation between patches is encoded in the FHMM framework via either interactive sampling or importance sampling over sets. Experimental results demonstrate that the proposed method qualitatively and quantitatively outperforms other methods, especially when the targets are highly deformable.
Databáze: Directory of Open Access Journals
Externí odkaz: