Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems
Faion, Florian
Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems - KIT Scientific Publishing 2016 - 1 electronic resource (XV, 197 p. p.)
Open Access
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.
Creative Commons
English
KSP/1000054248 9783731505174
10.5445/KSP/1000054248 doi
Tracking Bayesschätzer Microsoft Kinect Formschätzung Partial LikelihoodTracking Bayesian Estimation Microsoft Kinect Shape Fitting Partial Likelihood
Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems - KIT Scientific Publishing 2016 - 1 electronic resource (XV, 197 p. p.)
Open Access
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.
Creative Commons
English
KSP/1000054248 9783731505174
10.5445/KSP/1000054248 doi
Tracking Bayesschätzer Microsoft Kinect Formschätzung Partial LikelihoodTracking Bayesian Estimation Microsoft Kinect Shape Fitting Partial Likelihood