A Quantitative Analysis on Two RFS-Based Filtering Methods for Multicell Tracking
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-22
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Multiobject filters developed from the theory of random finite sets (RFS) have recently become well-known methods for solving multiobject tracking problem.
In this paper, we present two RFS-based filtering methods, Gaussian mixture probability hypothesis density (GM-PHD) filter and multi-Bernoulli filter, to quantitatively analyze their performance on tracking multiple cells in a series of low-contrast image sequences.
The GM-PHD filter, under linear Gaussian assumptions on the cell dynamics and birth process, applies the PHD recursion to propagate the posterior intensity in an analytic form, while the multi-Bernoulli filter estimates the multitarget posterior density through propagating the parameters of a multi-Bernoulli RFS that approximates the posterior density of multitarget RFS.
Numerous performance comparisons between the two RFS-based methods are carried out on two real cell images sequences and demonstrate that both yield satisfactory results that are in good agreement with manual tracking method.
American Psychological Association (APA)
Ren, Yayun& Xu, Benlian. 2014. A Quantitative Analysis on Two RFS-Based Filtering Methods for Multicell Tracking. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-476245
Modern Language Association (MLA)
Ren, Yayun& Xu, Benlian. A Quantitative Analysis on Two RFS-Based Filtering Methods for Multicell Tracking. Mathematical Problems in Engineering No. 2014 (2014), pp.1-17.
https://search.emarefa.net/detail/BIM-476245
American Medical Association (AMA)
Ren, Yayun& Xu, Benlian. A Quantitative Analysis on Two RFS-Based Filtering Methods for Multicell Tracking. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-476245
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-476245