000			01679naaaa2200253uu 4500
001			https://directory.doabooks.org/handle/20.500.12854/61100
005			20220220081759.0
020			_aKSP/1000054248
020			_a9783731505174
024	7		_a10.5445/KSP/1000054248 _cdoi
041	0		_aEnglish
042			_adc
100	1		_aFaion, Florian _4auth
245	1	0	_aTracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems
260			_bKIT Scientific Publishing _c2016
300			_a1 electronic resource (XV, 197 p. p.)
506	0		_aOpen Access _2star _fUnrestricted online access
520			_aWe 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.
540			_aCreative Commons _fhttps://creativecommons.org/licenses/by-sa/4.0/ _2cc _4https://creativecommons.org/licenses/by-sa/4.0/
546			_aEnglish
653			_aTracking Bayesschätzer Microsoft Kinect Formschätzung Partial LikelihoodTracking Bayesian Estimation Microsoft Kinect Shape Fitting Partial Likelihood
856	4	0	_awww.oapen.org _uhttps://www.ksp.kit.edu/9783731505174 _70 _zDOAB: download the publication
856	4	0	_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/61100 _70 _zDOAB: description of the publication
999			_c75517 _d75517