Message Passing Algorithms for Scalable Multitarget Tracking

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU130638" target="_blank" >RIV/00216305:26220/18:PU130638 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/JPROC.2018.2789427" target="_blank" >http://dx.doi.org/10.1109/JPROC.2018.2789427</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/JPROC.2018.2789427" target="_blank" >10.1109/JPROC.2018.2789427</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Message Passing Algorithms for Scalable Multitarget Tracking

Popis výsledku v původním jazyce

Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models.

Název v anglickém jazyce

Message Passing Algorithms for Scalable Multitarget Tracking

Popis výsledku anglicky

Situation-aware technologies enabled by multitarget tracking will lead to new services and applications in fields such as autonomous driving, indoor localization, robotic networks, and crowd counting. In this tutorial paper, we advocate a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum-product algorithm. This approach has advantages regarding estimation accuracy, computational complexity, and implementation flexibility. Most importantly, it provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitarget tracking. This fact makes it attractive for emerging applications requiring real-time operation on resource-limited devices. In addition, the message passing approach is intuitively appealing and suited to nonlinear and non-Gaussian models.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GA17-19638S" target="_blank" >GA17-19638S: Určování pohybu arteriální stěny pomocí sekvenčního bayesovského odhadu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

PROCEEDINGS OF THE IEEE

ISSN

0018-9219

e-ISSN

1558-2256

Svazek periodika

106

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

39

Strana od-do

221-259

Kód UT WoS článku

000425055600002

EID výsledku v databázi Scopus

2-s2.0-85042004490