Multiple target tracking from images using the maximum likelihood HPMHT

Document Type

Conference Proceeding

Publication Date

11-8-2013

Publication Title

Proceedings of SPIE - The International Society for Optical Engineering

Volume

8857

Keywords

Histogram PMHT, Minimum description length (MDL), Multi-target tracking, passive infrared (IR) images, point spread function (PSF)

Abstract

In this paper, we address the problem of passive tracking of multiple targets with the help of images obtained from passive infrared (IR) platforms. Conventional approaches to this problem, which involve thresholding, measurement detection, data association and filtering, encounter problems due to target energy being spread across multiple cells of the IR imagery. A histogram based probabilistic multi-hypothesis tracking (H-PMHT) approach provides an automatic means of modeling targets that are spread in multiple cells in the imaging sensor(s) by relaxing the need for hard decisions on measurement detection and data association. Further, we generalize the conventional HPMHT by adding an extra layer of EM iteration that yields the maximum likelihood (ML) estimate of the number of targets. With the help of simulated focal plane array (FPA) images, we demonstrate the applicability of MLHPMHT for enumerating and tracking multiple targets. © 2013 SPIE.

DOI

10.1117/12.2027297

ISSN

0277786X

E-ISSN

1996756X

ISBN

9780819497079

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