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Minimum distance between pattern transformation manifolds: Algorithm and Applications

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Form-finding Of Interlaced Space Structures

Yves Weinand, Seyed Sina Nabaei, Olivier Baverel

By Interlaced Space Structures (ISS) we mean a coupled system of naturally curved flexible panels/strips interlaced together according to a design pattern. We are looking for a physically-based and efficient form-finding procedure in order to interactively ...

2014

Inverse Rendering of Lambertian Surfaces Using Subspace Methods

Quy Ha Nguyen, Minh Do

We propose a vector space approach for inverse rendering of a Lambertian convex object with distant light sources. In this problem, the texture of the object and arbitrary lightings are both to be recovered from multiple images of the object and its 3D mod ...

Ieee-Inst Electrical Electronics Engineers Inc2014

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

Learning Smooth Pattern Transformation Manifolds

Pascal Frossard, Elif Vural

Manifold models provide low-dimensional representations that are useful for processing and analyzing data in a transformation-invariant way. In this paper, we study the problem of learning smooth pattern transformation manifolds from image sets that are ob ...

Institute of Electrical and Electronics Engineers2013

Approximate dynamic programming via sum of squares programming

Maryam Kamgarpour, Tyler Summers

We describe an approximate dynamic programming method for stochastic control problems on infinite state and input spaces. The optimal value function is approximated by a linear combination of basis functions with coefficients as decision variables. By rela ...

2013

An Iterative Linear Expansion of Thresholds for l1-based Image Restoration

Thierry Blu, Hanjie Pan

This paper proposes a novel algorithmic framework to solve image restoration problems under sparsity assumptions. As usual, the reconstructed image is the minimum of an objective functional that consists of a data fidelity term and an l1 regularization. Ho ...

Institute of Electrical and Electronics Engineers2013

Geometric Variational Models for Inverse Problems in Imaging

Virginia Estellers Casas

This dissertation develops geometric variational models for different inverse problems in imaging that are ill-posed, designing at the same time efficient numerical algorithms to compute their solutions. Variational methods solve inverse problems by the fo ...

EPFL2013

Blind Sensor Calibration in Sparse Recovery Using Convex Optimization

Rémi Gribonval, Gilles Puy

We investigate a compressive sensing system in which the sensors introduce a distortion to the measurements in the form of unknown gains. We focus on blind calibration, using measures performed on a few unknown (but sparse) signals. We extend our earlier s ...

2013

A convex optimization approach for image recovery from nonlinear measurements in optical interferometry

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Anna Auria Rasclosa

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bi-spectrum measurements. We formulate a linear version of the problem for the order-3 tensor formed by the tensor product of the ...

2013

Design and operations of gas transmission networks

Frédéric Louis François Babonneau

Problems dealing with the design and the operations of gas transmission networks are challenging. The difficulty mainly arises from the simultaneous modeling of gas transmission laws and of the investment costs. The combination of the two yields a non-line ...

2013