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Tracking Extended Objects in Noisy Point Clouds with Application in Telepresence Systems

By:

Faion, Florian [auth]

Material type: Article

ArticleLanguage: English Publication details: KIT Scientific Publishing 2016Description: 1 electronic resource (XV, 197 p. p.)ISBN:

KSP/1000054248
9783731505174

Subject(s):

Tracking Bayesschätzer Microsoft Kinect Formschätzung Partial LikelihoodTracking Bayesian Estimation Microsoft Kinect Shape Fitting Partial Likelihood

Online resources:

Summary: 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.

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Item type	Home library	Collection	Call number	Materials specified	Status	Date due	Barcode
Electronic-Books	OPJGU Sonepat- Campus	E-Books Open Access			Available

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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 https://creativecommons.org/licenses/by-sa/4.0/ cc https://creativecommons.org/licenses/by-sa/4.0/

English

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