scholarly journals Co-Reading as a Generative Ontology

2018 ◽  
Vol 6 (3) ◽  
pp. 151-163
Author(s):  
Simon Biggs
Keyword(s):  
Dark Matter ◽  
Motion Tracking ◽  
Interactive Systems ◽  
Body Motion ◽  
Interactive System ◽  
Assemblage Theory ◽  
Multi Agent ◽  
Technical Considerations ◽  
Full Body

This paper discusses the immersive full body motion tracking installation Dark Matter, developed by the author and completed in early 2016. The paper outlines the conceptual focus of the project, including the use of the metaphor of dark matter to explore questions around interactive systems and assemblage. The primary technical considerations involved in the project are also outlined. ‘Co-reading' is proposed as a framework for a generative ontology, within the context of assemblage theory, deployed within a multimodal multi-agent interactive system.

F2FCrowds: Planning Agent Movements to Enable Face-to-Face Interactions

2017 ◽  
Vol 26 (2) ◽  
pp. 228-246 ◽  
Author(s):  
Tanmay Randhavane ◽  
Aniket Bera ◽  
Dinesh Manocha
Keyword(s):  
User Study ◽  
Body Motion ◽  
Virtual Agents ◽  
Virtual Agent ◽  
Face To Face ◽  
Sense Of Presence ◽  
Velocity Prediction ◽  
Multi Agent ◽  
Interaction Velocity ◽  
Full Body

The simulation of human behaviors in virtual environments has many applications. In many of these applications, situations arise in which the user has a face-to-face interaction with a virtual agent. In this work, we present an approach for multi-agent navigation that facilitates a face-to-face interaction between a real user and a virtual agent that is part of a virtual crowd. In order to predict whether the real user is approaching a virtual agent to have a face-to-face interaction or not, we describe a model of approach behavior for virtual agents. We present a novel interaction velocity prediction (IVP) algorithm that is combined with human body motion synthesis constraints and facial actions to improve the behavioral realism of virtual agents. We combine these techniques with full-body virtual crowd simulation and evaluate their benefits by conducting a user study using Oculus HMD in an immersive environment. Results of this user study indicate that the virtual agents using our interaction algorithms appear more responsive and are able to elicit more reaction from the users. Our techniques thus enable face-to-face interactions between a real user and a virtual agent and improve the sense of presence observed by the user.

scholarly journals Embodied virtual reality for the study of real-world motor learning

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245717
Author(s):  
Shlomi Haar ◽  
Guhan Sundar ◽  
A. Aldo Faisal
Keyword(s):  
Virtual Reality ◽  
Motor Learning ◽  
Visual Feedback ◽  
Real World ◽  
Motion Tracking ◽  
Body Motion ◽  
Controlled Environment ◽  
Short Term ◽  
Learning And Adaptation ◽  
Full Body

Motor-learning literature focuses on simple laboratory-tasks due to their controlled manner and the ease to apply manipulations to induce learning and adaptation. Recently, we introduced a billiards paradigm and demonstrated the feasibility of real-world-neuroscience using wearables for naturalistic full-body motion-tracking and mobile-brain-imaging. Here we developed an embodied virtual-reality (VR) environment to our real-world billiards paradigm, which allows to control the visual feedback for this complex real-world task, while maintaining sense of embodiment. The setup was validated by comparing real-world ball trajectories with the trajectories of the virtual balls, calculated by the physics engine. We then ran our short-term motor learning protocol in the embodied VR. Subjects played billiard shots when they held the physical cue and hit a physical ball on the table while seeing it all in VR. We found comparable short-term motor learning trends in the embodied VR to those we previously reported in the physical real-world task. Embodied VR can be used for learning real-world tasks in a highly controlled environment which enables applying visual manipulations, common in laboratory-tasks and rehabilitation, to a real-world full-body task. Embodied VR enables to manipulate feedback and apply perturbations to isolate and assess interactions between specific motor-learning components, thus enabling addressing the current questions of motor-learning in real-world tasks. Such a setup can potentially be used for rehabilitation, where VR is gaining popularity but the transfer to the real-world is currently limited, presumably, due to the lack of embodiment.

scholarly journals A Hybrid Tracking System of Full-Body Motion Inside Crowds

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2108
Author(s):  
Maik Boltes ◽  
Juliane Adrian ◽  
Anna-Katharina Raytarowski
Keyword(s):  
Motion Tracking ◽  
Inertial Sensors ◽  
Tracking System ◽  
Body Motion ◽  
Whole Body ◽  
Body Parts ◽  
Movement Velocity ◽  
Camera System ◽  
Pedestrian Dynamics ◽  
Full Body

For our understanding of the dynamics inside crowds, reliable empirical data are needed, which could enable increases in safety and comfort for pedestrians and the design of models reflecting the real dynamics. A well-calibrated camera system can extract absolute head position with high accuracy. The inclusion of inertial sensors or even self-contained full-body motion capturing systems allows the relative tracking of invisible people or body parts or capturing the locomotion of the whole body even in dense crowds. The newly introduced hybrid system maps the trajectory of the top of the head coming from a full-body motion tracking system to the head trajectory of a camera system in global space. The fused data enable the analysis of possible correlations of all observables. In this paper we present an experiment of people passing though a bottleneck and show by example the influences of bottleneck width and motivation on the overall movement, velocity, stepping locomotion and rotation of the pelvis. The hybrid tracking system opens up new possibilities for analyzing pedestrian dynamics inside crowds, such as the space requirement while passing through a bottleneck. The system allows linking any body motion to characteristics describing the situation of a person inside a crowd, such as the density or movements of other participants nearby.

scholarly journals Embodied virtual reality for the study of real-world motor learning

2020 ◽  
Author(s):  
Shlomi Haar ◽  
Guhan Sundar ◽  
A. Aldo Faisal
Keyword(s):  
Virtual Reality ◽  
Motor Learning ◽  
Brain Imaging ◽  
Visual Feedback ◽  
Real World ◽  
Motion Tracking ◽  
Body Motion ◽  
Controlled Environment ◽  
Learning And Adaptation ◽  
Full Body

AbstractMotor-learning literature focuses on simple laboratory-tasks due to their controlled manner and the ease to apply manipulations to induce learning and adaptation. Recently, we introduced a billiards paradigm and demonstrated the feasibility of real-world-neuroscience using wearables for naturalistic full-body motion-tracking and mobile-brain-imaging. Here we developed an embodied virtual-reality (VR) environment to our real-world billiards paradigm, which allows to control the visual feedback for this complex real-world task, while maintaining sense of embodiment. The setup was validated by comparing real-world ball trajectories with the trajectories of the virtual balls, calculated by the physics engine. We then ran our learning protocol in the embodied VR. Subjects played billiard shots when they held the physical cue and hit a physical ball on the table while seeing it all in VR. We found comparable learning trends in the embodied VR to those we previously reported in the physical real-world task. Embodied VR can be used for learning real-world tasks in a highly controlled environment which enables applying visual manipulations, common in laboratory-tasks and rehabilitation, to a real-world full-body task. Embodied VR enables to manipulate feedback and apply perturbations to isolate and assess interactions between specific motor-learning components, thus enabling addressing the current questions of motor-learning in real-world tasks. Such a setup can be used for rehabilitation, where VR is gaining popularity but the transfer to the real-world is currently limited, presumably, due to the lack of embodiment.

scholarly journals Icy road ahead - rapid adjustments of gaze-gait interactions during perturbed naturalistic walking

2020 ◽  
Author(s):  
Karl K. Kopiske ◽  
Daniel Koska ◽  
Thomas Baumann ◽  
Christian Maiwald ◽  
Wolfgang Einhäuser
Keyword(s):  
Visual Information ◽  
Visual Cues ◽  
Motion Tracking ◽  
Head Movements ◽  
Body Motion ◽  
Naturalistic Environment ◽  
Stable Gait ◽  
Natural Terrain ◽  
Different Time Scales ◽  
Full Body

Most humans can walk effortlessly across uniform terrain even without paying much attention to it. However, most natural terrain is far from uniform, and we need visual information to maintain stable gait. In a controlled yet naturalistic environment, we simulated terrain difficulty through slip-like perturbations that were either unpredictable (experiment 1) or sometimes followed visual cues (experiment 2) while recording eye and body movements using mobile eye tracking and full-body motion tracking. We quantified the distinct roles of eye and head movements for adjusting gaze on different time scales. While motor perturbations mainly influenced head movements, eye movements were primarily affected by visual cues, both immediately following slips, and – to a lesser extent – over 5-minute blocks. We find adapted gaze parameters already after the first perturbation in each block, with little transfer between blocks. In conclusion, gaze-gait interactions in experimentally perturbed naturalistic walking are adaptive, flexible, and effector-specific.

Sign in / Sign up

Export Citation Format

Share Document