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Variational Maximum A Posteriori model similarity and dissimilarity matching

Research output: Chapter in Book/Report/Conference proceedingConference contribution

A new variational Maximum A Posteriori (MAP) contextual modeling approach is presented that minimizes the product of two ratios: (a) the ratio of the model distribution to the distribution of currently estimated foreground pixels; (b) the ratio of the background distribution to the model distribution for all estimated background pixels. This approach provides robust discrimination to identify the division between foreground and background pixels, which is useful for applications such as object tracking.
Original languageEnglish
Title of host publication19th International conference on pattern recognition, 2008. ICPR 2008
Place of PublicationPiscataway
PublisherIEEE/ IAPR
Pages1-4
ISBN (Electronic)9781424421756
ISBN (Print)9781424421749
DOIs
Publication statusPublished - 1 Dec 2008
Event19th International conference on pattern recognition - Florida, United States
Duration: 8 Dec 200811 Dec 2008

Conference

Conference19th International conference on pattern recognition
Abbreviated titleICPR 2008
CountryUnited States
CityFlorida
Period8/12/0811/12/08

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ID: 1562024