Results 221 to 230 of about 113,691 (269)

Manifold clustering

Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005
Manifold learning has become a vital tool in data driven methods for interpretation of video, motion capture, and handwritten character data when they lie on a low dimensional, nonlinear manifold. This work extends manifold learning to classify and parameterize unlabeled data which lie on multiple, intersecting manifolds.
Souvenir, Richard, Pless, Robert
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ON INTERPOLATION IN MANIFOLDS

International Journal of Shape Modeling, 1996
We suggest a general method for one-dimensional interpolation in general manifolds, which allows to produce interpolation of arbitrary smoothness; interpolation in the group of orthogonal 3 × 3 matrices and the group of isometries of the three dimensional space using the exponential mapping is described as an example of application of this general ...
G. G. Okuneva, Oleg G. Okunev, Karol Myszkowski, Tosiyasu L. Kunii   +3 more
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The approximation of closed manifolds by triangulated manifolds and the triangulation of closed manifolds

Computing, 1992
For the closed surface \(\Gamma\) in \(\mathbb{R}^ 3\) given by the local parameter representation \(f_ i: \Omega_ i\to\mathbb{R}^ 3\) with \(\Omega_ i\) open domains in \(\mathbb{R}^ 2\), \(i=1,\dots,p\), the authors construct an \(h\) parameter-dependent family \(\Gamma_ h\) of approximations to \(\Gamma\) such that \(\Gamma_ h\) is a triangulated ...
K. Kalik, Wolfgang L. Wendland
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On the Structure of Manifolds

American Journal of Mathematics, 1962
In this paper, we prove a number of theorems which give some insight into the structure of differentiable manifolds. The methods, results and some notation of [13], hereafter referred to as GPC, and [12] will be used. These two papers and [14] can be considered as a starting point for this one. The main theorems in these papers are special cases of the
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Deep Manifold-to-Manifold Transforming Network

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
In this paper, we propose an end-to-end deep manifold-to-manifold transforming network (DMT-Net), which makes SPD matrices flow from one Riemannian manifold to another more discriminative one. For discriminative feature learning, two specific layers on manifolds are developed: (i) the local SPD convolutional layer, (ii) the non-linear SPD activation ...
Tong Zhang 0021, Wenming Zheng, Zhen Cui 0001, Chaolong Li   +3 more
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Computing the Stable Manifold of a Saddle Slow Manifold

SIAM Journal on Applied Dynamical Systems, 2018
An algorithm for computing an accurate approximation of the stable manifold of a saddle slow manifold (SSM) is developed. The case of slow-fast systems with one slow and two fast variables is considered and an example is presented. A similar approach is used for its stable and unstable manifolds.
Saeed Farjami, Vivien Kirk, Hinke M. Osinga   +2 more
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Geometric Manifold Energy and Manifold Clustering

2009
A general nonparametric technique is proposed for the description of geometric manifold energy of unorganized data. Minimizing the energy leads to an optimal cycle, from which underlying manifolds are easily distinguished. We design a new framework for manifold clustering based on energy minimization.
Hongyu Li 0001, Qiyong Guo, Jinyuan Jia, Jussi Parkkinen   +3 more
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