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» Manifold Clustering of Shapes
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ISBI
2008
IEEE
14 years 9 months ago
Deformation-based nonlinear dimension reduction: Applications to nuclear morphometry
We describe a new approach for elucidating the nonlinear degrees of freedom in a distribution of shapes depicted in digital images. By combining a deformation-based method for mea...
Gustavo K. Rohde, Wei Wang, Tao Peng, Robert F. Mu...
SCALESPACE
2009
Springer
14 years 3 months ago
Pre-image as Karcher Mean Using Diffusion Maps: Application to Shape and Image Denoising
In the context of shape and image modeling by manifold learning, we focus on the problem of denoising. A set of shapes or images being known through given samples, we capture its s...
Nicolas Thorstensen, Florent Ségonne, Renau...
ICPR
2008
IEEE
14 years 2 months ago
A novel validity measure for clusters of arbitrary shapes and densities
Several validity indices have been designed to evaluate solutions obtained by clustering algorithms. Traditional indices are generally designed to evaluate center-based clustering...
Noha A. Yousri, Mohamed S. Kamel, Mohamed A. Ismai...
CSIE
2009
IEEE
14 years 3 months ago
Evaluating Clustering Algorithms: Cluster Quality and Feature Selection in Content-Based Image Clustering
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Ward’s method, with the latter three being different hierarchical...
Mesfin Sileshi, Björn Gambäck
ICML
2005
IEEE
14 years 9 months ago
Implicit surface modelling as an eigenvalue problem
We discuss the problem of fitting an implicit shape model to a set of points sampled from a co-dimension one manifold of arbitrary topology. The method solves a non-convex optimis...
Christian Walder, Olivier Chapelle, Bernhard Sch&o...