-- Monday, 11 June 2012 at 14:00 (45 min.)
{
"name":"High Level Markov Modeling and Markov Random Tree recognition",
"description":"Markov Random Field (MRF) modeling is a powerful framework allowing to formulate and to solve very complex imaging problems. This talk presents a particular case of MRF: the High Level MRF with application to root segmentation. This framework enables to formulate features based matching. The structures to recognize are assimilated to Markov Random Trees. A curves formulation aims to reduce the solution space and implement complex metrics. Results will be presented on data base and isolate images.",
"startDate":"2012-06-11",
"endDate":"2012-06-11",
"startTime":"14:00",
"endTime":"14:45",
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"timeZone":"Europe/Berlin",
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Markov Random Field (MRF) modeling is a powerful framework allowing to formulate and to solve very complex imaging problems. This talk presents a particular case of MRF: the High Level MRF with application to root segmentation. This framework enables to formulate features based matching. The structures to recognize are assimilated to Markov Random Trees. A curves formulation aims to reduce the solution space and implement complex metrics. Results will be presented on data base and isolate images.
