Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Statistical shape analysis

Publications associées (26)

A novel measurement of marginal Alfven eigenmode stability during high power auxiliary heating in JET

Ambrogio Fasoli, Mario Ludovico Podesta, Paulo Giovane Paschoali Pereira Puglia

The interaction of Alfven eigenmodes (AEs) and energetic particles is one of many important factors determining the success of future tokamaks. In JET, eight in-vessel antennas were installed to actively probe stable AEs with frequencies ranging 25-250 kHz ...

IOP Publishing Ltd2022

Learning Self-Exciting Temporal Point Processes Under Noisy Observations

William Trouleau

Understanding the diffusion patterns of sequences of interdependent events is a central question for a variety of disciplines. Temporal point processes are a class of elegant and powerful models of such sequences; these processes have become popular across ...

EPFL2021

Remodeling of brain morphology in temporal lobe epilepsy

Lester Melie Garcia

Background Mesial temporal lobe epilepsy (TLE) is one of the most widespread neurological network disorders. Computational anatomy MRI studies demonstrate a robust pattern of cortical volume loss. Most statistical analyses provide information about localiz ...

2020

Procrustes Metrics on Covariance Operators and Optimal Transportation of Gaussian Processes

Victor Panaretos, Yoav Zemel, Valentina Masarotto

Covariance operators are fundamental in functional data analysis, providing the canonical means to analyse functional variation via the celebrated Karhunen-Loeve expansion. These operators may themselves be subject to variation, for instance in contexts wh ...

2019

Procrustes Metrics and Optimal Transport for Covariance Operators

Valentina Masarotto

Covariance operators play a fundamental role in functional data analysis, providing the canonical means to analyse functional variation via the celebrated Karhunen-Loève expansion. These operators may themselves be subject to variation, for instance in con ...

EPFL2019

Automated CT bone segmentation using statistical shape modelling and local template matching

Alexandre Terrier, Alain Farron, Philippe Büchler

Accurate CT bone segmentation is essential to develop chair-side manufacturing of implants based on additive manufacturing. We herewith present an automated method able to accurately segment challenging bone regions, while simultaneously providing anatomic ...

2019

Fréchet means and Procrustes analysis in Wasserstein space

Victor Panaretos, Yoav Zemel

We consider two statistical problems at the intersection of functional and non-Euclidean data analysis: the determination of a Fréchet mean in the Wasserstein space of multivariate distributions; and the optimal registration of deformed random measures and ...

2019

A finite element framework based on bivariate simplex splines on triangle configurations

Xiaodong Wei

Recently, triangle configuration based bivariate simplex splines (referred to as TCB-spline) have been introduced to the geometric computing community. TCB-splines retain many attractive theoretic properties of classical B-splines, such as partition of uni ...

ELSEVIER SCIENCE SA2019

Landmark-Based Shape Encoding and Sparse-Dictionary Learning in the Continuous Domain

Michaël Unser, Daniel Andreas Schmitter

We provide a generic framework to learn shape dictionaries of landmark-based curves that are defined in the continuous domain. We first present an unbiased alignment method that involves the construction of a mean shape as well as training sets whose eleme ...

2018

Machine-learning methods for weak lensing analysis of the ESA Euclid sky survey

Thibault Adrien Kuntzer

A clear picture has emerged from the last three decades of research: our Universe is expanding at an accelerated rate. The cause of this expansion remains elusive, but in essence acts as a repulsive force. This so-called dark energy represents about 69% of ...

EPFL2018

Neuronal morphologies: the shapes of thoughts

Lida Kanari

The mammalian brain, one of the most fascinating systems in nature, is a complex biological structure that has kept scientists busy for over a century. Many of the brain's mysteries have been unraveled due to the enormous efforts of the scientific communit ...

EPFL2018

Discovering Structured Variations Via Template Matching

Mark Pauly, Duygu Ceylan, Boris Neubert

Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. Such an understanding reveals which elements are repeated, or how elements can be derived as structured variations from a common base element. We invest ...

2017

Spline Shape Processing : Representation, Learning, and Modeling

Daniel Andreas Schmitter

In this thesis, we present a novel generic and unifying framework for data-adaptive shape modeling. Our work is motivated by the raising need for powerful geometric modeling kernels that are required for shape characterization in biomedical imaging. The on ...

EPFL2017

Template-based Monocular 3-D Shape Reconstruction And Tracking Using Laplacian Meshes

Tien Dat Ngo

This thesis addresses the problem of recovering the 3-D shape of a deformable object in single images, or image sequences acquired by a monocular video camera, given that a 3-D template shape and a template image of the object are available. While being a ...

EPFL2016

Template-free 3D Reconstruction of Poorly-textured Nonrigid Surfaces

Mathieu Salzmann, Xinchao Wang

Two main classes of approaches have been studied to perform monocular nonrigid 3D reconstruction: Template-based methods and Non-rigid Structure from Motion techniques. While the first ones have been applied to reconstruct poorly-textured surfaces, they as ...

Springer Int Publishing Ag2016

Smoothly Deformable Spheres: Modeling, Deformation, and Interaction

Michaël Unser, Daniel Andreas Schmitter

Existing shape models with spherical topology are typically designed either in the discrete domain using interpolating polygon meshes or in the continuous domain using smooth but non-interpolating schemes such as NURBS. Polygon models and subdivision metho ...

ACM2016

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

Dense image registration and deformable surface reconstruction in presence of occlusions and minimal texture

Pascal Fua, Alberto Crivellaro, Tien Dat Ngo, Anne Alison Jorstad

Deformable surface tracking from monocular images is well-known to be under-constrained. Occlusions often make the task even more challenging, and can result in failure if the surface is not sufficiently textured. In this work, we explicitly address the pr ...

2015

Trigonometric Interpolation Kernel to Construct Deformable Shapes for User-Interactive Applications

Michaël Unser, Daniel Andreas Schmitter, Ricard Delgado Gonzalo

We present a new trigonometric basis function that is capable of perfectly reproducing circles, spheres and ellipsoids while at the same time being interpolatory. Such basis functions have the advantage that they allow to construct shapes through a sequenc ...

IEEE Institute of Electrical and Electronics Engineers2015

Discovering Structured Variations via Coupled Template Matching

Mark Pauly, Duygu Ceylan, Boris Neubert, Ngoc Minh Dang

Understanding patterns of variation from raw measurement data remains a central goal of shape analysis. This understanding reveals which elements are exactly repeated, or how elements can be derived as structured variations from a common base element. We i ...

2016