Journal of Mathematical Imaging and Vision
Size functions for comparing 3D models
Pattern Recognition
Describing shapes by geometrical-topological properties of real functions
ACM Computing Surveys (CSUR)
Multidimensional Size Functions for Shape Comparison
Journal of Mathematical Imaging and Vision
Simploidals sets: Definitions, operations and comparison with simplicial sets
Discrete Applied Mathematics
Computation of homology groups and generators
Computers and Graphics
Homological Computation Using Spanning Trees
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Computing homology: a global reduction approach
DGCI'09 Proceedings of the 15th IAPR international conference on Discrete geometry for computer imagery
Morse connections graph for shape representation
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
Computation of homology groups and generators
DGCI'05 Proceedings of the 12th international conference on Discrete Geometry for Computer Imagery
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In this paper, we propose a new topological method for shape description that is suitable for any multi-dimensional data set that can be modelled as a manifold.The description is obtained for all pairs (M, f), where M is a closed smooth manifold and f a Morse function defined on M.More precisely, we characterize the topology of all pairs of lower level sets (M_y, M_x) of f, where M_a = f^{-1} ((-驴, a]), for all a 驴 R.Classical Morse theory is used to establish a link between the topology of a pair of lower level sets of f and its critical points lying between the two levels.