Matches in SemOpenAlex for { <https://semopenalex.org/work/W1968650122> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W1968650122 abstract "Interest in shapes of 3D objects naturally leads to shape analysis of curves and surfaces. The theme of this talk is Riemannian frameworks that offer certain distinct advantages. In addition to providing measures for shape comparisons, clustering and retrieval, a Riemannian framework also provides optimal deformations between shapes, statistical averaging of observed shapes, and probabilistic modeling of shapes in different shape classes. The use of such a framework involves the following issues. Firstly, one needs to be invariant to reparameterizations, in addition to the standard shape-preserving transformations of rigid motions and global scalings. The solution is to use mathematical representations (of curves and surfaces) and elastic Riemannian metrics such that re-parameterization groups act by isometries. Secondly, one needs tools for computing geodesic paths between given objects in shape spaces. We have developed a numerical method, called pathstraightening, for this purpose. Next, one needs tools for computing sample statistics. We have adapted definitions and techniques from statistical analysis on Riemannian manifolds for computing means and covariances of shapes. Further, we have used these moments in defining Gaussian-type distributions on shape spaces. These models are useful in statistical shape classification, hypothesis testing and Bayesian shape extractions from images. From the perspective of shape retrieval, these tools contribute in hierarchical organizations of shape databases and shape metrics that relate to probabilistic models for shape classes. This framework is general enough to incorporate other information, such as landmarks, colors, or other annotations along the shapes in the analysis. I will demonstrate these ideas using examples from vision, biometrics, bioinformatics, and medical image analysis. This work has been done in collaboration with several researchers." @default.
- W1968650122 created "2016-06-24" @default.
- W1968650122 creator A5086786635 @default.
- W1968650122 date "2010-10-25" @default.
- W1968650122 modified "2023-09-27" @default.
- W1968650122 title "Elastic Riemannian frameworks and statistical tools for shape analysis" @default.
- W1968650122 doi "https://doi.org/10.1145/1877808.1877809" @default.
- W1968650122 hasPublicationYear "2010" @default.
- W1968650122 type Work @default.
- W1968650122 sameAs 1968650122 @default.
- W1968650122 citedByCount "0" @default.
- W1968650122 crossrefType "proceedings-article" @default.
- W1968650122 hasAuthorship W1968650122A5086786635 @default.
- W1968650122 hasConcept C109546454 @default.
- W1968650122 hasConcept C112604564 @default.
- W1968650122 hasConcept C11413529 @default.
- W1968650122 hasConcept C114289077 @default.
- W1968650122 hasConcept C12520029 @default.
- W1968650122 hasConcept C12713177 @default.
- W1968650122 hasConcept C129641003 @default.
- W1968650122 hasConcept C154945302 @default.
- W1968650122 hasConcept C165818556 @default.
- W1968650122 hasConcept C181104567 @default.
- W1968650122 hasConcept C190470478 @default.
- W1968650122 hasConcept C195065555 @default.
- W1968650122 hasConcept C199360897 @default.
- W1968650122 hasConcept C2524010 @default.
- W1968650122 hasConcept C33923547 @default.
- W1968650122 hasConcept C37914503 @default.
- W1968650122 hasConcept C41008148 @default.
- W1968650122 hasConcept C45089102 @default.
- W1968650122 hasConcept C49937458 @default.
- W1968650122 hasConcept C73555534 @default.
- W1968650122 hasConcept C89600930 @default.
- W1968650122 hasConcept C97686452 @default.
- W1968650122 hasConceptScore W1968650122C109546454 @default.
- W1968650122 hasConceptScore W1968650122C112604564 @default.
- W1968650122 hasConceptScore W1968650122C11413529 @default.
- W1968650122 hasConceptScore W1968650122C114289077 @default.
- W1968650122 hasConceptScore W1968650122C12520029 @default.
- W1968650122 hasConceptScore W1968650122C12713177 @default.
- W1968650122 hasConceptScore W1968650122C129641003 @default.
- W1968650122 hasConceptScore W1968650122C154945302 @default.
- W1968650122 hasConceptScore W1968650122C165818556 @default.
- W1968650122 hasConceptScore W1968650122C181104567 @default.
- W1968650122 hasConceptScore W1968650122C190470478 @default.
- W1968650122 hasConceptScore W1968650122C195065555 @default.
- W1968650122 hasConceptScore W1968650122C199360897 @default.
- W1968650122 hasConceptScore W1968650122C2524010 @default.
- W1968650122 hasConceptScore W1968650122C33923547 @default.
- W1968650122 hasConceptScore W1968650122C37914503 @default.
- W1968650122 hasConceptScore W1968650122C41008148 @default.
- W1968650122 hasConceptScore W1968650122C45089102 @default.
- W1968650122 hasConceptScore W1968650122C49937458 @default.
- W1968650122 hasConceptScore W1968650122C73555534 @default.
- W1968650122 hasConceptScore W1968650122C89600930 @default.
- W1968650122 hasConceptScore W1968650122C97686452 @default.
- W1968650122 hasLocation W19686501221 @default.
- W1968650122 hasOpenAccess W1968650122 @default.
- W1968650122 hasPrimaryLocation W19686501221 @default.
- W1968650122 hasRelatedWork W1968596169 @default.
- W1968650122 hasRelatedWork W1985880123 @default.
- W1968650122 hasRelatedWork W2059917035 @default.
- W1968650122 hasRelatedWork W2103104276 @default.
- W1968650122 hasRelatedWork W2111093365 @default.
- W1968650122 hasRelatedWork W2125882322 @default.
- W1968650122 hasRelatedWork W2126962853 @default.
- W1968650122 hasRelatedWork W2212089300 @default.
- W1968650122 hasRelatedWork W3137963709 @default.
- W1968650122 hasRelatedWork W4250800977 @default.
- W1968650122 isParatext "false" @default.
- W1968650122 isRetracted "false" @default.
- W1968650122 magId "1968650122" @default.
- W1968650122 workType "article" @default.