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Low-order graphical models for shapes and hierarchies in segmentation

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VMVW03 - Flows, mappings and shapes

This talks discusses simple (low-order) graphical models imposing practically powerful constraints on shapes and hierarchical structure of segments in the context of binary and multi-object labeling of images. We discuss properties and optimization for generic shape priors like “star”, geodesic star, hedgehog, as well as models for partially-ordered labeling of interacting objects. While the talk focuses on biomedical applications where structural constraints (shapes and hierarchy) come from anatomy, the discussed general graphical models are useful for semi-supervised computer vision problems. Related papers appeared at CVPR 2017 , 2016, ICCV 2009 , 2005, ECCV 2008 .

This talk is part of the Isaac Newton Institute Seminar Series series.

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