1,685 research outputs found
Hierarchy construction schemes within the Scale set framework
Segmentation algorithms based on an energy minimisation framework often
depend on a scale parameter which balances a fit to data and a regularising
term. Irregular pyramids are defined as a stack of graphs successively reduced.
Within this framework, the scale is often defined implicitly as the height in
the pyramid. However, each level of an irregular pyramid can not usually be
readily associated to the global optimum of an energy or a global criterion on
the base level graph. This last drawback is addressed by the scale set
framework designed by Guigues. The methods designed by this author allow to
build a hierarchy and to design cuts within this hierarchy which globally
minimise an energy. This paper studies the influence of the construction scheme
of the initial hierarchy on the resulting optimal cuts. We propose one
sequential and one parallel method with two variations within both. Our
sequential methods provide partitions near the global optima while parallel
methods require less execution times than the sequential method of Guigues even
on sequential machines
Contains and Inside relationships within combinatorial Pyramids
Irregular pyramids are made of a stack of successively reduced graphs
embedded in the plane. Such pyramids are used within the segmentation framework
to encode a hierarchy of partitions. The different graph models used within the
irregular pyramid framework encode different types of relationships between
regions. This paper compares different graph models used within the irregular
pyramid framework according to a set of relationships between regions. We also
define a new algorithm based on a pyramid of combinatorial maps which allows to
determine if one region contains the other using only local calculus.Comment: 35 page
Efficient Encoding of n-D Combinatorial Pyramids
International audienceCombinatorial maps define a general framework which allows to encode any subdivision of an n-D orientable quasi-manifold with or without boundaries. Combinatorial pyramids are defined as stacks of successively reduced combinatorial maps. Such pyramids provide a rich framework which allows to encode fine properties of objects (either shapes or partitions). Combinatorial pyramids have first been defined in 2D, then extended using n-D generalized combinatorial maps. We motivate and present here an implicit and efficient way to encode pyramids of n-D combinatorial maps
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