Objektsensitive Verfolgung und Klassifikation von Fußgängern mit verteilten Multi-Sensor-Trägern
Pallauf, Johannes
Objektsensitive Verfolgung und Klassifikation von Fußgängern mit verteilten Multi-Sensor-Trägern - KIT Scientific Publishing 2016 - 1 electronic resource (XI, 178 p. p.)
Open Access
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.
Creative Commons
German
KSP/1000054659 9783731505297
10.5445/KSP/1000054659 doi
Multi-Objekt-Verfolgung verteilte Systeme SensorenMulti-object-tracking sensors Objektklassifikation object classification pedestrian tracking distributed systems Personenverfolgung
Objektsensitive Verfolgung und Klassifikation von Fußgängern mit verteilten Multi-Sensor-Trägern - KIT Scientific Publishing 2016 - 1 electronic resource (XI, 178 p. p.)
Open Access
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.
Creative Commons
German
KSP/1000054659 9783731505297
10.5445/KSP/1000054659 doi
Multi-Objekt-Verfolgung verteilte Systeme SensorenMulti-object-tracking sensors Objektklassifikation object classification pedestrian tracking distributed systems Personenverfolgung