Add to ORKGWhen shapes of objects are modeled as topologicalspaces endowed with functions, the shape comparison problem canbe dealt with using persistent homology to provide shape descriptors,and the matching distance to measure dissimilarities. Motivatedby the problem of dealing with incomplete or imprecise acquisitionof data in computer vision and computer graphics, recentpapers have studied stability properties of persistent Betti numbers with respect to perturbations both in the topological space and in the function. This paper reports on progress in this area of research
The ability to perform not only global matching but also partial matching is investigated in compute...
In content-based image retrieval a major problem is the presence of noisy shapes. Noise can present...
Topological Persistence has proven to be a promising framework for dealing with problems concerning ...
When shapes of objects are modeled as topologicalspaces endowed with functions, the shape comparison...
When shapes of objects are modeled as topological spaces endowed with functions, the shape compariso...
Persistence is a theory for Topological Data Analysis based on analyzing the scale at whichtopologic...
Persistent homology has proven itself quite efficient in the topological and qualitative comparison ...
The theory of multidimensional persistent homology was initially developed in the discrete setting, ...
Persistent homology provides shapes descriptors called persistence diagrams. We use persistence diag...
The theory of multidimensional persistent homology was initially developed in the discrete setting, ...
none1noClassical persistent homology is a powerful mathematical tool for shape comparison. Unfortuna...
Multidimensional persistence mostly studies topological features of shapes by analyzing the lower le...
In this paper, we initiate a study of shape description and classification via the application of pe...
In content-based image retrieval a major problem is the presence of noisy shapes. It is well known t...
The ability to perform not only global matching but also partial matching is investigated in compute...
In content-based image retrieval a major problem is the presence of noisy shapes. Noise can present...
Topological Persistence has proven to be a promising framework for dealing with problems concerning ...
When shapes of objects are modeled as topologicalspaces endowed with functions, the shape comparison...
When shapes of objects are modeled as topological spaces endowed with functions, the shape compariso...
Persistence is a theory for Topological Data Analysis based on analyzing the scale at whichtopologic...
Persistent homology has proven itself quite efficient in the topological and qualitative comparison ...
The theory of multidimensional persistent homology was initially developed in the discrete setting, ...
Persistent homology provides shapes descriptors called persistence diagrams. We use persistence diag...
The theory of multidimensional persistent homology was initially developed in the discrete setting, ...
none1noClassical persistent homology is a powerful mathematical tool for shape comparison. Unfortuna...
Multidimensional persistence mostly studies topological features of shapes by analyzing the lower le...
In this paper, we initiate a study of shape description and classification via the application of pe...
In content-based image retrieval a major problem is the presence of noisy shapes. It is well known t...
The ability to perform not only global matching but also partial matching is investigated in compute...
In content-based image retrieval a major problem is the presence of noisy shapes. Noise can present...
Topological Persistence has proven to be a promising framework for dealing with problems concerning ...