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https://hdl.handle.net/2440/58138
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Vo, B. | - |
dc.contributor.author | Vo, B. | - |
dc.contributor.author | Suter, D. | - |
dc.contributor.author | Pham, N. | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | Proceedings from the 12th International Conference on Information Fusion Seattle, WA, USA, July 6-9, 2009: pp.890-898. | - |
dc.identifier.isbn | 9780982443804 | - |
dc.identifier.uri | http://hdl.handle.net/2440/58138 | - |
dc.description.abstract | Analytic characterizations of the posterior distribution of a random finite set of states, conditioned on image observations are derived; under the assumption that the regions of the observation influenced by individual states do not overlap. These results provide tractable means to jointly estimate the number of states and their values in the Bayesian framework. As an application, we develop a multiobject filter suitable for image observations with low signal to noise ratio. A particle implementation of the multi-object filter is proposed and demonstrated via simulations. | - |
dc.description.statementofresponsibility | Ba-Ngu Vo, Ba-Tuong Vo, David Suter and Nam Trung Pham | - |
dc.language.iso | en | - |
dc.publisher | IEEE | - |
dc.rights | ©2009 ISIF | - |
dc.subject | Random sets | - |
dc.subject | Multi-Bernoulli | - |
dc.subject | Filtering | - |
dc.subject | Images | - |
dc.subject | Tracking | - |
dc.subject | Track Before Detect | - |
dc.title | Bayesian multi-object estimation from image observations | - |
dc.type | Conference paper | - |
dc.contributor.conference | International Conference on Information Fusion (12th : 2009 : Seattle, USA) | - |
dc.publisher.place | USA | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Suter, D. [0000-0001-6306-3023] | - |
Appears in Collections: | Aurora harvest Computer Science publications |
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