Publications related to Motion Pattern Encapsulation for Data-Driven Constraint-Based Motion Editing

Related publications (24)

From finger animation to full-body embodiment of avatars with different morphologies and proportions

VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world. This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR. At the advent of ...

EPFL2023

Automated Human Motion Analysis and Synthesis

Sena Kiciroglu

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

EPFL2023

Real-time Self-contact Retargeting of Avatars down to Finger Level

Ronan Boulic, Bruno Herbelin, Mathias Guy Delahaye

We interact with the world through a body that includes hands and fingers. Likewise, providing an avatar allowing the control of a virtual body with fingers is an important step to improve the user experience in VR. When the user and their avatar skeleton ...

The Eurographics Association2023

Microgravity induces overconfidence in perceptual decision-making

Davide Scaramuzza, Christian Pfeiffer, Leyla Loued-Khenissi

Does gravity affect decision-making? This question comes into sharp focus as plans for interplanetary human space missions solidify. In the framework of Bayesian brain theories, gravity encapsulates a strong prior, anchoring agents to a reference frame via ...

Nature Portfolio2023

Processing load, and not stimulus evidence, determines the duration of unconscious visual feature integration

Michael Herzog, Leila Drissi Daoudi - Kleinbauer, Lukas Vogelsang

Integration across space and time is essential for the analysis of motion, low contrast, and many more stimuli. A crucial question is what determines the duration of integration. Based on classical models of decision-making, one might expect that integrati ...

2023

Encoder-Decoder Models for Human Segmentation and Motion Analysis

Isinsu Katircioglu

Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...

EPFL2022

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

Dual-Arm Control for Coordinated Fast Grabbing and Tossing of an Object

Aude Billard, Michael Bosongo Bombile

Picking up objects to toss them on a conveyor belt are activities generated on a daily basis in the industry. These tasks are still done largely by humans. This paper proposes a unified motion generator for a bimanual robotic systems that enables two 7 deg ...

2022

Explanation of Optical Force and Torque on Nanomotors as the Interplay of Huygens Sources

Olivier Martin, Karim Achouri, Mintae Chung

Being able to understand how optical forces emerge from the interaction of light with matter is paramount for controlling the motion of nanoparticles as well as powering nanomotors. The purpose of this work is to uncover the physical mechanisms at the orig ...

IEEE2022

Preventing Breaks in Embodiment in Immersive Virtual Reality

Thibault Serge Mario Porssut

Virtual reality (VR) is immersive not only because of visual integration, but because we can act and perform in a virtual environment (VE). Beyond the mere fact that a VR system provides images computed directly from the users' viewpoint in stereoscopy, it ...

EPFL2021

Analysis and Modeling of the Dynamics of Traction Forces during Cell Polarization and their Role in the Organization of Edge Activity

Zeno Messi

The capacity to break symmetry and organize activity to move directionally is a fundamental property of eukaryotic cells. To explain the organization of cell-edge activity, models commonly rely on front-to-back gradients of functional components or regulat ...

EPFL2021

Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Mathieu Salzmann

Recent progress in stochastic motion prediction, i.e., predicting multiple possible future human motions given a single past pose sequence, has led to producing truly diverse future motions and even providing control over the motion of some body parts. How ...

IEEE2021

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Dario Floreano, Fabrizio Schiano

We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector o ...

2021

Fat navigators based retrospective motion correction strategies for brain magnetic resonance imaging

Frédéric Gretsch

Magnetic resonance resonance (MRI) is a widely used modality to obtain in vivo tissue information. Clinical applications are near countless, and almost all body parts can be examined using an MR scanner. As the method is non invasive, does not use ionizing ...

EPFL2020

Propulsion module for generating wave-like motion

Auke Ijspeert, Peter Eckert, Mohammadreza Bayat

The present invention relates to a propulsion module (1) for generating wave-like motion in liquid. The propulsion module (1) comprises: a motor (7) for generating rotational motion; a set of conversion devices comprising a first conversion device (91) and ...

2020

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

Neural Scene Decomposition for Multi-Person Motion Capture

Pascal Fua, Mathieu Salzmann, Helge Jochen Rhodin, Isinsu Katircioglu, Victor Constantin

Learning general image representations has proven key to the success of many computer vision tasks. For example, many approaches to image understanding problems rely on deep networks that were initially trained on ImageNet, mostly because the learned featu ...

IEEE2019

Reconciling Being in-Control vs. Being Helped for the Execution of Complex Movements in VR

Ronan Boulic, Bruno Herbelin, Thibault Serge Mario Porssut

Performing motor tasks in virtual environments is best achieved with motion capture and animation of a 3D character that participants control in real time and perceive as being their avatar in the virtual environment. A strong Sense of Embodiment (SoE) for ...

IEEE2019

Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks

Daniel Thalmann, Hui Liang

In this paper, we present a novel method for real-time 3D hand pose estimation from single depth images using 3D Convolutional Neural Networks (CNNs). Image-based features extracted by 2D CNNs are not directly suitable for 3D hand pose estimation due to th ...

IEEE COMPUTER SOC2019

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