Density morphing and mode propagation for Bayesian filtering

A system and method for modeling a dynamic system using Bayesian filtering, includes a prediction module to predict a state model of the dynamic system, the prediction module generates a prediction density having at least one mode, the state model includes a conditional density function including at...

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Bibliographic Details
Main Authors HAN BOHYUNG, ZHU YING, COMANICIU DORIN
Format Patent
LanguageEnglish
Published 17.02.2005
Edition7
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
CONTROL OR REGULATING SYSTEMS IN GENERAL
CONTROLLING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
FUNCTIONAL ELEMENTS OF SUCH SYSTEMS
MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS
PHYSICS
REGULATING
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Summary:A system and method for modeling a dynamic system using Bayesian filtering, includes a prediction module to predict a state model of the dynamic system, the prediction module generates a prediction density having at least one mode, the state model includes a conditional density function including at least one kernel. Approximating module approximates a measurement probability from a sample set through at least one kernel and an update module updates the conditional density function using the measurement probability and the prediction density. A mode finding and mixture reduction module reduces the number of kernels in the conditional density function.
Bibliography:Application Number: US20040896512