Factored particle filtering with dependent and constrained partition dynamics for tracking deformable objects

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Tarih

2014-10

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Springer

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Araştırma projeleri

Organizasyon Birimleri

Dergi sayısı

Özet

In particle filtering, dimensionality of the state space can be reduced by tracking control (or feature) points as independent objects, which are traditionally named as partitions. Two critical decisions have to be made in implementation of reduced state-space dimensionality. First is how to construct a dynamic (transition) model for partitions that are inherently dependent. Second critical decision is how to filter partition states such that a viable and likely object state is achieved. In this study, we present a correlation-based transition model and a proposal function that incorporate partition dependency in particle filtering in a computationally tractable manner. We test our algorithm on challenging examples of occlusion, clutter and drastic changes in relative speeds of partitions. Our successful results with as low as 10 particles per partition indicate that the proposed algorithm is both robust and efficient.

Açıklama

Anahtar Kelimeler

Particle filtering, Condensation, Factorized likelihoods, Deterministic drift, Proposal function, Multiple objects, Integration

Kaynak

Machine Vision and Applications

WoS Q Değeri

Q2
Q2

Scopus Q Değeri

Q2

Cilt

25

Sayı

7

Künye

Eskil, M. T. (2014). Factored particle filtering with dependent and constrained partition dynamics for tracking deformable objects. Machine Vision and Applications, 25(7), 1825-1840. doi:10.1007/s00138-014-0634-1