Remarkable local resampling based on particle filter for visual tracking
Remarkable local resampling based on particle filter for visual tracking
About this item
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Author / Creator
Publisher
New York: Springer US
Journal title
Language
English
Formats
Publication information
Publisher
New York: Springer US
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More information
Scope and Contents
Contents
Generally, particle filters need a large number of particles to approximate the posterior for the purpose of ideal effect. Previous methods extract remarkable particles from the particles at time
t
-1 by nonlinear function. Those methods use the remarkable particles to reduce the number of particles and improve the accuracy of particle filter...
Alternative Titles
Full title
Remarkable local resampling based on particle filter for visual tracking
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_proquest_miscellaneous_1880005055
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1880005055
Other Identifiers
ISSN
1380-7501
E-ISSN
1573-7721
DOI
10.1007/s11042-015-3075-6
