Visual tracking using interactive factorial hidden Markov models

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 geom...

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Bibliographic Details
Main Authors: Jin Wook Paeng, Junseok Kwon
Format: Article
Language:English
Published: Wiley 2021-08-01
Series:IET Signal Processing
Subjects:
Online Access:https://doi.org/10.1049/sil2.12037
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Summary: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.
ISSN:1751-9675
1751-9683