Multiobject Tracking with Track Continuity: An Efficient Random Finite Set Based Algorithm
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Multiobject Tracking with Track Continuity: An Efficient Random Finite Set Based Algorithm
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20202 - Communication engineering and systems
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2018 SYMPOSIUM ON SENSOR DATA FUSION: TRENDS, SOLUTIONS, APPLICATIONS (SDF)
ISBN
978-1-5386-9398-8
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
1-6
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
neuveden
Event location
Bonn
Event date
Oct 9, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000458573700003