Multi-Target Joint Detection; Tracking and Classification Based on Marginal GLMB Filter and Belief Function Theory

This paper proposes a new solution to multi-target joint detection, tracking and classification based on labeled random finite set (RFS) and belief function theory. A class dependent multi-model marginal generalized labeled multi-Bernoulli (MGLMB) filter is developed to analytically calculate the mu...

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Detalles Bibliográficos
Autores principales: Liang, Jun, Li, Minzhe, Jing, Zhongliang, Pan, Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435813/
https://www.ncbi.nlm.nih.gov/pubmed/32751386
http://dx.doi.org/10.3390/s20154235

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435813/
https://www.ncbi.nlm.nih.gov/pubmed/32751386
http://dx.doi.org/10.3390/s20154235

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