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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Bibliographic Details
Published in:International journal of advanced robotic systems 2016-06, Vol.13 (3)
Main Authors: Zhu, Hao, Hu, Jinsong, Leung, Henry, Zhang, Bin
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Bias
Computer simulation
Estimates
Methods
Noise
Parameter estimation
Performance evaluation
Recursive methods
Registration
Sensors
Signal processing
Statistical inference
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Summary: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.
ISSN:1729-8806
1729-8814
DOI:10.5772/64012