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• W1534612841 abstract "Domaine : Mathematiques appliquees, calcul et simulationEquipes-Projets PERCEPTIONRapport de recherche n ° 7090  October 2009  17 pagesAbstract:This paper deals with the stereo matching problem, while moving away fromthe traditional fronto-parallel assumption. We propose an algorithm that pro-vides disparities in accordance with the surface properties of the scene underconsideration. To do so, we carry out cooperatively both disparity and surfacenormal estimations by setting the two tasks in a unied Markovian framework.A novel joint probabilistic model is dened through two Markov Random Fields(MRF) to favor both intra eld (within neighboring disparities and neighboringnormals) and inter eld (between disparities and normals) consistency. Geomet-ric contextual information is introduced in the pair-wise Markovian regularizingterm used in both MRFs. Segmentation and plane tting procedures, usuallyperformed as nal steps to increase the quality results are here explicitly usedin one of the MRF data terms. We then design an appropriate alternating max-imization procedure based on standard Belief Propagation. We illustrate theperformance of our approach on synthetic and real data. The results obtainedare comparable to the state-of-the-art and show improvement in many cases.Key-words: Stereo vision, Markov Random Fields, Belief propagation Alter-nating Maximization" @default.
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• W1534612841 date "2009-10-01" @default.
• W1534612841 modified "2023-09-23" @default.
• W1534612841 title "A Joint Framework for Disparity and Surface Normal Estimation" @default.
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