Publications associées à Variété (géométrie)

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Principal Flows

Victor Panaretos, Tung Huy Pham, Zhigang Yao

We revisit the problem of extending the notion of principal component analysis (PCA) to multivariate datasets that satisfy nonlinear constraints, therefore lying on Riemannian manifolds. Our aim is to determine curves on the manifold that retain their cano ...

American Statistical Association2014

Principal Polynomial Analysis

Devis Tuia

This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of ma ...

World Scientific Publ Co Pte Ltd2014

Total Variation Regularization for Manifold-Valued Data

Martin Kurt Storath

We consider total variation (TV) minimization for manifold-valued data. We propose a cyclic proximal point algorithm and a parallel proximal point algorithm to minimize TV functionals with l(p) -type data terms in the manifold case. These algorithms are ba ...

Siam Publications2014

Harmonic Active Contours

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso, Virginia Estellers Casas

We propose a segmentation method based on the geometric representation of images as two-dimensional manifolds embedded in a higher dimensional space. The segmentation is formulated as a minimization problem, where the contours are described by a level set ...

Institute of Electrical and Electronics Engineers2014

Tangent-based manifold approximation with locally linear models

Pascal Frossard, Sofia Karygianni

In this paper, we consider the problem of manifold approximation with affine subspaces. Our objective is to discover a set of low dimensional affine subspaces that represent manifold data accurately while preserving the manifold's structure. For this purpo ...

Elsevier2014

Non-linear Low-rank and Sparse Representation for Hyperspectral Image Analysis

Jean-Philippe Thiran, Devis Tuia, Volker Gass, Frank Grégoire Jean de Morsier, Maurice Borgeaud

In this paper, we tackle the problem of unsupervised classification of hyperspectral images. We propose a clustering method based on graphs representing the data structure, which is assumed to be an union of multiple manifolds. The method constraints the p ...

2014

Semisupervised Manifold Alignment of Multimodal Remote Sensing Images

Devis Tuia, Maxime Pierre Trolliet

We introduce a method for manifold alignment of different modalities (or domains) of remote sensing images. The problem is recurrent when a set of multitemporal, multisource, multisensor, and multiangular images is available. In these situations, images sh ...

Ieee-Inst Electrical Electronics Engineers Inc2014

Electrostatics of solvated systems in periodic boundary conditions

Nicola Marzari, Oliviero Andreussi

Continuum solvation methods can provide an accurate and inexpensive embedding of quantum simulations in liquid or complex dielectric environments. Notwithstanding a long history and manifold applications to isolated systems in open boundary conditions, the ...

Amer Physical Soc2014

Variété (géométrie)

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Chattez avec Graph Search

Principal Flows

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Principal Polynomial Analysis

Total Variation Regularization for Manifold-Valued Data

Harmonic Active Contours

Tangent-based manifold approximation with locally linear models

Non-linear Low-rank and Sparse Representation for Hyperspectral Image Analysis

Semisupervised Manifold Alignment of Multimodal Remote Sensing Images

Electrostatics of solvated systems in periodic boundary conditions

Graph-based Image Inpainting

Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images

Tangent-based manifold approximation with locally linear models

Principal Flows

Semisupervised Manifold Alignment of Multimodal Remote Sensing Images

Electrostatics of solvated systems in periodic boundary conditions

Principal Polynomial Analysis

Harmonic Active Contours

Non-linear Low-rank and Sparse Representation for Hyperspectral Image Analysis

Total Variation Regularization for Manifold-Valued Data

Graph-based Image Inpainting