TY  - GEN
AU  - Faion,Florian
TI  - Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems
SN  - KSP/1000054248
PY  - 2016///
PB  - KIT Scientific Publishing
KW  - Tracking Bayesschätzer Microsoft Kinect Formschätzung Partial LikelihoodTracking Bayesian Estimation Microsoft Kinect Shape Fitting Partial Likelihood
N1  - Open Access
N2  - We discuss theory and application of extended object tracking. This task is challenging as sensor noise prevents a correct association of the measurements to their sources on the object, the shape itself might be unknown a priori, and due to occlusion effects, only parts of the object are visible at a given time. We propose an approach to track the parameters of arbitrary objects, which provides new solutions to the above challenges, and marks a significant advance to the state of the art
UR  - https://www.ksp.kit.edu/9783731505174
UR  - https://directory.doabooks.org/handle/20.500.12854/61100
ER  -