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Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

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Data-driven Measurement Designs for Magnetic Resonance Imaging

Baran Gözcü

Despite being a powerful medical imaging technique which does not emit any ionizing radiation, magnetic resonance imaging (MRI) always had the major problem of long scanning times that can take up to an hour depending on the application. It also requires u ...

EPFL2019

Long Term Motion Prediction Using Keyposes

Pascal Fua, Mathieu Salzmann, Wei Wang, Sena Kiciroglu

Long term human motion prediction is essential in safety-critical applications such as human-robot interaction and autonomous driving. In this paper we show that to achieve long term forecasting, predicting human pose at every time instant is unnecessary. ...

IEEE2022

Improving the arm-hand coordination in neuroprosthetics control with prior information from muscle activity

Iason Batzianoulis

Humans use their hands mainly for grasping and manipulating objects, performing simple and dexterous tasks. The loss of a hand may significantly affect one's working status and independence in daily life. A restoration of the grasping ability is important ...

EPFL2019

Textual Explanations and Critiques in Recommendation Systems

Diego Matteo Antognini

Artificial intelligence and machine learning algorithms have become ubiquitous. Although they offer a wide range of benefits, their adoption in decision-critical fields is limited by their lack of interpretability, particularly with textual data. Moreover, ...

EPFL2022

Gravity as a Reference for Estimating a Person's Height from Video

Pascal Fua, Helge Jochen Rhodin, Semih Günel

Estimating the metric height of a person from monocular imagery without additional assumptions is ill-posed. Existing solutions either require manual calibration of ground plane and camera geometry, special cameras, or reference objects of known size. We f ...

IEEE2019

Multi-fidelity regression using artificial neural networks: Efficient approximation of parameter-dependent output quantities

Jan Sickmann Hesthaven

Highly accurate numerical or physical experiments are often very time-consuming or expensive to obtain. When time or budget restrictions prohibit the generation of additional data, the amount of available samples may be too limited to provide satisfactory ...

ELSEVIER SCIENCE SA2022

Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion

Purpose: Head movements are a major source of MRI artefacts. Prospective motion correction techniques significantly improve data quality, but strong motion artefacts may remain in the data. We introduce a framework to suspend data acquisition during period ...

Wiley2018

Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach

Giancarlo Ferrari Trecate, Luca Furieri, Muhammad Zakwan, Clara Lucía Galimberti

Large-scale cyber-physical systems require that control policies are distributed, that is, that they only rely on local real-time measurements and communication with neighboring agents. Optimal Distributed Control (ODC) problems are, however, highly intrac ...

2022

Perspectives in machine learning for wildlife conservation

Devis Tuia, Alexander Mathis, Mackenzie Mathis, Benjamin Alexander Kellenberger

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill data into ...

Nature Research2022

Flight Dynamics-based Recovery of a UAV Trajectory using Ground Cameras

Pascal Fua, Artem Rozantsev

We propose a new method to estimate the 6-dof trajectory of a flying object such as a quadrotor UAV within a 3D airspace monitored using multiple fixed ground cameras. It is based on a new structure from motion formulation for the 3D reconstruction of a si ...

Ieee2017

Unpredictability does not hamper nonretinotopic motion perception

Michael Herzog, Marc Michael Lauffs

The motion of parts of an object is usually perceived relative to the object, i.e., nonretinotopically, rather than in retinal coordinates. For example, we perceive a reflector to rotate on the wheel of a moving bicycle even though its trajectory is cycloi ...

Association for Research in Vision and Ophthalmology (ARVO)2017

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Beril Besbinar

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

EPFL2022

Gaia Data Release 1 Open cluster astrometry: performance, limitations, and future prospects

Stephan Morgenthaler, Shuangqing Liao

Context. The first Gaia Data Release contains the Tycho-Gaia Astrometric Solution (TGAS). This is a subset of about 2 million stars for which, besides the position and photometry, the proper motion and parallax are calculated using Hipparcos and Tycho-2 po ...

Edp Sciences S A2017

Numerical and experimental investigation of spiral-grooved gas journal bearings

Elia Iseli

Small-scale turbomachinery is increasingly used in carbon-free energy conversion systems, such as commercial or domestic scale heat pumps, fuels cells for transportation and waste heat recovery. The usage of aerodynamic bearings allows the design of compac ...

EPFL2022

Learning Externally Modulated Dynamical Systems

Aude Billard, Klas Jonas Alfred Kronander, Nicolas Sommer

Dynamical Systems (DS) are often used to represent motion, with the advantage of being easy to learn from demonstrations. We present a method to modulate DS depending on an external signal, extending our previous work on Locally Modulated DS (LMDS, Kronand ...

2017

Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion

Yufan Ren

This paper proposes a representational model for image pairs such as consecutive video frames that are related by local pixel displacements, in the hope that the model may shed light on motion perception in primary visual cortex (V1). The model couples the ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

Next generation modeling techniques for strong gravitational lensing and measuring the Hubble constant

Aymeric Alexandre Galan

For many years, observations of the Universe suggest a series problems with our theoretical models, particularly its dark energy and dark matter components. Fortunately, the Universe also provides us with a tool to solve these problems, called strong gravi ...

EPFL2022

Motion-based nearest vector metric for reference frame selection in the perception of motion

Michael Herzog, Aaron Michael Clarke

We investigated how the visual system selects a reference frame for the perception of motion. Two concentric arcs underwent circular motion around the center of the display, where observers fixated. The outer (target) arc's angular velocity profile was mod ...

Association for Research in Vision and Ophthalmology (ARVO)2016

Prospective motion correction in kidney MRI using FID navigators

Tobias Kober

Purpose Abdominal MRI scans may require breath-holding to prevent image quality degradation, which can be challenging for patients, especially children. In this study, we evaluate whether FID navigators can be used to measure and correct for motion prospec ...

WILEY2022

Stellar kinematics using a third integral of motion: method and application on the Andromeda galaxy

Olga Tihhonova

We probe the feasibility of describing the structure of a multicomponent axisymmetric galaxy with a dynamical model based on the Jeans equations while taking into account a third integral of motion. We demonstrate that using the third integral in the form ...

Oxford Univ Press2016