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Title: "High Level Markov Modeling and Markov Random Tree recognition"

Speaker: Jerome Plumat

Date / Time (duration): Monday 11/6/2012, 14h00 (~ 45')

Place: TVNUM Seminar room

(Place du Levant 2, Stevin Building, 1st floor)

Abstract: 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.

Last updated September 25, 2013, at 09:08 AM