TY  - BOOK
AU  - Pallauf, Johannes
AB  - State estimation of an unknown number of objects remains a challenging topic - despite the existence of theoretically bayes-optimal multi-object-filters - due to numerous assumptions in the modeling process. This thesis evaluates such filters in real multi-object-multi-sensor scenarios and proposes necessary extensions to existing models. The main application of the thesis is indoor pedestrian tracking.
DO  - 10.5445/KSP/1000054659
ID  - OAPEN ID: 34501
KW  - Multi-Objekt-Verfolgung
KW  - verteilte Systeme
KW  - SensorenMulti-object-tracking
KW  - sensors
KW  - Objektklassifikation
KW  - object classification
KW  - pedestrian tracking
KW  - distributed systems
KW  - Personenverfolgung
L1  - https://www.ksp.kit.edu/9783731505297
LA  - German
LK  - https://directory.doabooks.org/handle/20.500.12854/55091
PB  - KIT Scientific Publishing
PY  - 2016
SN  - 9783731505297
TI  - Objektsensitive Verfolgung und Klassifikation von Fußgängern mit verteilten Multi-Sensor-Trägernnull
ER  - 
