Multiobject Tracking with Track Continuity: An Efficient Random Finite Set Based Algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU136304" target="_blank" >RIV/00216305:26220/18:PU136304 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/8547059" target="_blank" >https://ieeexplore.ieee.org/document/8547059</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SDF.2018.8547059" target="_blank" >10.1109/SDF.2018.8547059</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multiobject Tracking with Track Continuity: An Efficient Random Finite Set Based Algorithm

Popis výsledku v původním jazyce

We propose a random finite set (RFS) based algorithm for tracking multiple objects while maintaining track continuity. In our approach, the object states are modeled by a combination of a labeled multi-Bernoulli (LMB) RFS and a Poisson RFS. Low complexity is achieved through several judiciously chosen approximations in the update step. In particular, the computationally less demanding Poisson part of our algorithm is used to track potential objects whose existence is highly uncertain. A new labeled Bernoulli component is generated only if there is sufficient evidence of object existence, and then the corresponding object state is tracked by the more accurate but more complex LMB part of the algorithm. Simulation results for a challenging scenario demonstrate an attractive accuracy-complexity tradeoff and a significant complexity reduction relative to other RFS-based algorithms with comparable performance.

Název v anglickém jazyce

Multiobject Tracking with Track Continuity: An Efficient Random Finite Set Based Algorithm

Popis výsledku anglicky

We propose a random finite set (RFS) based algorithm for tracking multiple objects while maintaining track continuity. In our approach, the object states are modeled by a combination of a labeled multi-Bernoulli (LMB) RFS and a Poisson RFS. Low complexity is achieved through several judiciously chosen approximations in the update step. In particular, the computationally less demanding Poisson part of our algorithm is used to track potential objects whose existence is highly uncertain. A new labeled Bernoulli component is generated only if there is sufficient evidence of object existence, and then the corresponding object state is tracked by the more accurate but more complex LMB part of the algorithm. Simulation results for a challenging scenario demonstrate an attractive accuracy-complexity tradeoff and a significant complexity reduction relative to other RFS-based algorithms with comparable performance.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20202 - Communication engineering and systems

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

2018 SYMPOSIUM ON SENSOR DATA FUSION: TRENDS, SOLUTIONS, APPLICATIONS (SDF)

ISBN

978-1-5386-9398-8

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

Institute of Electrical and Electronics Engineers Inc.

Místo vydání

neuveden

Místo konání akce

Bonn

Datum konání akce

9. 10. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000458573700003