Engineering Statistics for Multi-Object Tracking

Authors:
Ronald Mahler
Affiliations:
-
Venue:
WOMOT '01 Proceedings of the IEEE Workshop on Multi-Object Tracking (WOMOT'01)
Year:
2001

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Abstract

Abstracts: Progress in single-sensor, single-object tracking has been greatly facilitated by the existence of a systematic, rigorous, and yet practical engineering statistics that supports the development of new concepts. Surprisingly, until recently no similar engineering statistics has been available for multi-sensor, multi-object tracking. I describe the Bayes filtering equations (the theoretical basis for all optimal single-sensor, single-object tracking) and explain why their generalization to multisensor-multitarget problems requires systematic engineering statistics---i.e., finite-set statistics (FSST). I conclude by summarizing the main concepts of FSST---in particular, the multisensor-multitarget differential and integral calculus that is its core.