Publications associées à Reaching and grasping kitchenware objects

Publications associées (25)

Aggregating Spatial and Photometric Context for Photometric Stereo

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

EPFL2024

Unfreezing Social Navigation: Dynamical Systems based Compliance for Contact Control in Robot Navigation

Aude Billard, Diego Felipe Paez Granados, Vaibhav Gupta

Large efforts have focused on ensuring that the controllers for mobile service robots follow proxemics and other social rules to ensure both safe and socially acceptable distance to pedestrians. Nonetheless, involuntary contact may be unavoidable when the ...

IEEE2022

Robust Differentiable SVD

Pascal Fua, Mathieu Salzmann, Wei Wang, Yinlin Hu, Zheng Dang

Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) ...

2021

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks

David Atienza Alonso, José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao

Decoding the subjective perception of task difficulty may help improve operator performance, i.e., automatically optimize the task difficulty level. Here, we aim to decode a compound of cognitive states that covaries with the task difficulty level. We desi ...

2020

Turbulent patterns in wall-bounded shear flows: invariant solutions and their bifurcations

Florian Reetz

When laminar shear flows in large wall-bounded domains transition to turbulence, the flow exhibits spatio-temporally chaotic dynamics. Despite its chaotic dynamics, the flow may self-organize into characteristic spatially periodic patterns of unknown origi ...

EPFL2019

Learning Robust Features and Latent Representations for Single View 3D Pose Estimation of Humans and Objects

Bugra Tekin

Estimating the 3D poses of rigid and articulated bodies is one of the fundamental problems of Computer Vision. It has a broad range of applications including augmented reality, surveillance, animation and human-computer interaction. Despite the ever-growin ...

EPFL2018

Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses

Pascal Fua, Mathieu Salzmann, Kwang Moo Yi, Yinlin Hu, Zheng Dang

Many classical Computer Vision problems, such as essential matrix computation and pose estimation from 3D to 2D correspondences, can be solved by ﬁnding the eigenvector corresponding to the smallest, or zero, eigenvalue of a matrix representing a linear sy ...

2018

Guidelines on nonlinear dynamic analysis for seismic design of steel moment frames

Dimitrios Lignos

Nonlinear dynamic (response history) analysis is being used increasingly in design practice for the performance-based seismic design of buildings. In contrast to nonlinear static analysis, dynamic analyses require more explicit modeling of cyclic response ...

2018

Dynamical Behavior and Stability Analysis of Hydromechanical Gates

Paolo Perona, Fabian Alexander Bernhard

This study revisits the stability of hydromechanical gates for upstream water surface regulation, also known as AMIL gates. AMIL gates are used in irrigation canals, where they are often installed in series. From the regulation perspective, instabilities a ...

American Society of Civil Engineers2017

Noether Theorems and Quantum Anomalies

Tudor Ratiu

A quantum anomaly is the breaking of symmetry with respect to some transformations after the quantization of a classical Hamiltonian or Lagrangian system. It is shown that both the Noether theorems (including their infinite-dimensional versions) and the ex ...

Springer Verlag2017

Scalable Low-rank Matrix and Tensor Decomposition on Graphs

Nauman Shahid

In many signal processing, machine learning and computer vision applications, one often has to deal with high dimensional and big datasets such as images, videos, web content, etc. The data can come in various forms, such as univariate or multivariate time ...

EPFL2017

Robust 3D Object Pose Estimation and Tracking from Monocular Images in Industrial Environments

Alberto Crivellaro

Recent advances in Computer Vision are changing our way of living and enabling new applications for both leisure and professional use. Regrettably, in many industrial domains the spread of state-of-the-art technologies is made challenging by the abundance ...

EPFL2016

Fast Robust PCA on Graphs

Pierre Vandergheynst, Gilles Puy, Nathanaël Perraudin, Vasilis Kalofolias, Nauman Shahid

Mining useful clusters from high dimensional data has received significant attention of the computer vision and pattern recognition community in the recent years. Linear and non-linear dimensionality reduction has played an important role to overcome the c ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Optimality of Operator-Like Wavelets for Representing Sparse AR(1) Processes

Michaël Unser, Pedram Pad

The discrete cosine transform (DCT) is known to be asymptotically equivalent to the Karhunen-Loève transform (KLT) of Gaussian first-order auto-regressive (AR(1)) processes. Since being uncorrelated under the Gaussian hypothesis is synonymous with independ ...

IEEE2015

Musculoskeletal Model of the Human Shoulder for Joint Force Estimation

David Ingram

Human beings like all organisms, are subject to a variety of diseases. Musculoskeletal diseases such as arthritis, that affect our muscles and bones, are particularly debilitating in that they considerably limit our ability to interact with our environment ...

EPFL2015

Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

Auke Ijspeert

Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear ...

Massachusetts Institute of Technology Press2013

Particle-hole condensates of higher angular momentum in hexagonal systems

Ronny Thomale

Hexagonal lattice systems (e.g., triangular, honeycomb, kagome) possess a multidimensional irreducible representation corresponding to d(x2-y2) and d(xy) symmetry. Consequently, various unconventional phases that combine these d-wave representations can oc ...

Amer Physical Soc2013

Multivariate statistical analysis as a tool for the segmentation of 3D spectral data

Cécile Hébert, Marco Cantoni, Guillaume Lucas, Pierre Burdet

Acquisition of three-dimensional (3D) spectral data is nowadays common using many different microanalytical techniques. In order to proceed to the 3D reconstruction, data processing is necessary not only to deal with noisy acquisitions but also to segment ...

Pergamon-Elsevier Science Ltd2013

Networks of Self-Adaptive Dynamical Systems

Max-Olivier Hongler, Julio Rodriguez

We discuss the adaptive behaviour of a collection of heterogeneous dynamical systems interacting via a weighted network. At each vertex, the network is endowed with a dynamical system with individual (initially different) control parameters governing the l ...

Oxford University Press2012

Maximal symmetrization and reduction of fields: Application to wave functions in solid-state nanostructures

Marc-André Dupertuis, Sascha Dalessi

A general formalism for the maximal symmetrization and reduction of fields (MSRFs) is proposed and applied to wave functions in solid-state nanostructures. Its primary target is to provide an essential tool for the study and analysis of the electronic and ...

2010