The shape function can be approximated as a disjunction of conjunctions, using the disjunctive normal form. The shape model is initialized using seed points ...
In this paper, we propose a novel parametric, implicit shape model which we call the Disjunctive Normal Shape Model (DNSM). We approximate the characteristic ...
Disjunctive normal shape models. Abstract: A novel implicit parametric shape model is proposed for segmentation and analysis of medical images. Functions ...
A novel implicit parametric shape model is proposed for segmentation and analysis of medical images. Functions representing the shape of an object can be ...
In this paper, we present a novel shape and appearance priors for image seg- mentation based on an implicit parametric shape representation called disjunctive ...
Disjunctive Normal Shape Model (DNSM) is a differentiable implicit and parametric shape model where the parameters of the model are the angles and positions ...
Disjunctive Normal Shape Model (DNSM) is a strong shape model that can effectively represent local parts of objects. In this paper, we propose a new shape model ...
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Active shape models are parametric deformable models which sta- tistically capture the variations of shapes in the provided training data. These models are also ...
Functions representing the shape of an object can be approximated as a union of N polytopes. Each polytope is obtained by the intersection of M half-spaces. The ...
Mar 9, 2017 · Disjunctive Normal Shape Model (DNSM) is a strong shape representation that can effectively represent local parts of objects. Shape Boltzmann ...