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dc.contributor.authorFaion, Florian*
dc.date.accessioned2021-02-12T06:13:43Z
dc.date.available2021-02-12T06:13:43Z
dc.date.issued2016*
dc.date.submitted2019-07-30 20:02:01*
dc.identifier35413*
dc.identifier.issn18673813*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/61100
dc.description.abstractWe 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.*
dc.languageEnglish*
dc.relation.ispartofseriesKarlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory*
dc.subjectT1-995*
dc.subject.otherTracking Bayesschätzer Microsoft Kinect Formschätzung Partial LikelihoodTracking Bayesian Estimation Microsoft Kinect Shape Fitting Partial Likelihood*
dc.titleTracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000054248*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
oapen.relation.isbn9783731505174*
oapen.pagesXV, 197 p.*
oapen.volume19*


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