Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion

In this paper, we propose a novel simultaneous registration and fusion approach for tracking. This method is based on a recursive Variational Bayesian (RVB) algorithm, which is the online variant of the Variational Bayesian (VB) approach. Under the Bayesian framework, the states and parameters are r...

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Main Authors:	Hao Zhu, Jinsong Hu, Henry Leung, Bin Zhang
Format:	Article
Language:	English
Published:	SAGE Publishing 2016-06-01
Series:	International Journal of Advanced Robotic Systems
Online Access:	https://doi.org/10.5772/64012

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record_format	Article
spelling	doaj-99e8332edc994c8f9cf9e8a927e7f5572020-11-25T03:15:32ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142016-06-011310.5772/6401210.5772_64012Recursive Variational Bayesian Inference to Simultaneous Registration and FusionHao Zhu0Jinsong Hu1Henry Leung2Bin Zhang3 Chongqing University of Posts and Telecommunications, Chongqing, China Chongqing University of Posts and Telecommunications, Chongqing, China University of Calgary, Calgary, Canada Chongqing University of Posts and Telecommunications, Chongqing, ChinaIn this paper, we propose a novel simultaneous registration and fusion approach for tracking. This method is based on a recursive Variational Bayesian (RVB) algorithm, which is the online variant of the Variational Bayesian (VB) approach. Under the Bayesian framework, the states and parameters are recursively estimated. It is shown by simulation that the proposed RVB method has better estimation performance than the conventional approach.https://doi.org/10.5772/64012
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Hao Zhu Jinsong Hu Henry Leung Bin Zhang
spellingShingle	Hao Zhu Jinsong Hu Henry Leung Bin Zhang Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion International Journal of Advanced Robotic Systems
author_facet	Hao Zhu Jinsong Hu Henry Leung Bin Zhang
author_sort	Hao Zhu
title	Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion
title_short	Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion
title_full	Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion
title_fullStr	Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion
title_full_unstemmed	Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion
title_sort	recursive variational bayesian inference to simultaneous registration and fusion
publisher	SAGE Publishing
series	International Journal of Advanced Robotic Systems
issn	1729-8814
publishDate	2016-06-01
description	In this paper, we propose a novel simultaneous registration and fusion approach for tracking. This method is based on a recursive Variational Bayesian (RVB) algorithm, which is the online variant of the Variational Bayesian (VB) approach. Under the Bayesian framework, the states and parameters are recursively estimated. It is shown by simulation that the proposed RVB method has better estimation performance than the conventional approach.
url	https://doi.org/10.5772/64012
work_keys_str_mv	AT haozhu recursivevariationalbayesianinferencetosimultaneousregistrationandfusion AT jinsonghu recursivevariationalbayesianinferencetosimultaneousregistrationandfusion AT henryleung recursivevariationalbayesianinferencetosimultaneousregistrationandfusion AT binzhang recursivevariationalbayesianinferencetosimultaneousregistrationandfusion
_version_	1724638945530085376

Recursive Variational Bayesian Inference to Simultaneous Registration and Fusion

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