6,459 research outputs found
Exploring the Design Space of Immersive Urban Analytics
Recent years have witnessed the rapid development and wide adoption of
immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft
HoloLens. These immersive devices have the potential to significantly extend
the methodology of urban visual analytics by providing critical 3D context
information and creating a sense of presence. In this paper, we propose an
theoretical model to characterize the visualizations in immersive urban
analytics. Further more, based on our comprehensive and concise model, we
contribute a typology of combination methods of 2D and 3D visualizations that
distinguish between linked views, embedded views, and mixed views. We also
propose a supporting guideline to assist users in selecting a proper view under
certain circumstances by considering visual geometry and spatial distribution
of the 2D and 3D visualizations. Finally, based on existing works, possible
future research opportunities are explored and discussed.Comment: 23 pages,11 figure
A framework for realistic 3D tele-immersion
Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite differ- ent from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experi- ence of talking in person. Several causes for these differences have been identified and we propose inspiring and innova- tive solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational expe- rience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic ex- periences to a multitude of users that for them will feel much more similar to having face to face meetings than the expe- rience offered by conventional teleconferencing systems
Supporting ethnographic studies of ubiquitous computing in the wild
Ethnography has become a staple feature of IT research over the last twenty years, shaping our understanding of the social character of computing systems and informing their design in a wide variety of settings. The emergence of ubiquitous computing raises new challenges for ethnography however, distributing interaction across a burgeoning array of small, mobile devices and online environments which exploit invisible sensing systems. Understanding interaction requires ethnographers to reconcile interactions that are, for example, distributed across devices on the street with online interactions in order to assemble coherent understandings of the social character and purchase of ubiquitous computing systems. We draw upon four recent studies to show how ethnographers are replaying system recordings of interaction alongside existing resources such as video recordings to do this and identify key challenges that need to be met to support ethnographic study of ubiquitous computing in the wild
Enabling collaboration in virtual reality navigators
In this paper we characterize a feature superset for Collaborative
Virtual Reality Environments (CVRE), and derive a component
framework to transform stand-alone VR navigators into full-fledged
multithreaded collaborative environments. The contributions of our
approach rely on a cost-effective and extensible technique for
loading software components into separate POSIX threads for
rendering, user interaction and network communications, and adding a
top layer for managing session collaboration. The framework recasts
a VR navigator under a distributed peer-to-peer topology for scene
and object sharing, using callback hooks for broadcasting remote
events and multicamera perspective sharing with avatar interaction.
We validate the framework by applying it to our own ALICE VR
Navigator. Experimental results show that our approach has good
performance in the collaborative inspection of complex models.Postprint (published version
The SISO CSPI PDG standard for commercial off-the-shelf simulation package interoperability reference models
For many years discrete-event simulation has been used to analyze production and logistics problems in manufactur-ing and defense. Commercial-off-the-shelf Simulation Packages (CSPs), visual interactive modelling environ-ments such as Arena, Anylogic, Flexsim, Simul8, Witness, etc., support the development, experimentation and visua-lization of simulation models. There have been various attempts to create distributed simulations with these CSPs and their tools, some with the High Level Architecture (HLA). These are complex and it is quite difficult to assess how a set of models/CSP are actually interoperating. As the first in a series of standards aimed at standardizing how the HLA is used to support CSP distributed simula-tions, the Simulation Interoperability Standards Organiza-tionâs (SISO) CSP Interoperability Product Development Group (CSPI PDG) has developed and standardized a set of Interoperability Reference Models (IRM) that are in-tended to clearly identify the interoperability capabilities of CSP distributed simulations
Self-Synchronization in Duty-cycled Internet of Things (IoT) Applications
In recent years, the networks of low-power devices have gained popularity.
Typically these devices are wireless and interact to form large networks such
as the Machine to Machine (M2M) networks, Internet of Things (IoT), Wearable
Computing, and Wireless Sensor Networks. The collaboration among these devices
is a key to achieving the full potential of these networks. A major problem in
this field is to guarantee robust communication between elements while keeping
the whole network energy efficient. In this paper, we introduce an extended and
improved emergent broadcast slot (EBS) scheme, which facilitates collaboration
for robust communication and is energy efficient. In the EBS, nodes
communication unit remains in sleeping mode and are awake just to communicate.
The EBS scheme is fully decentralized, that is, nodes coordinate their wake-up
window in partially overlapped manner within each duty-cycle to avoid message
collisions. We show the theoretical convergence behavior of the scheme, which
is confirmed through real test-bed experimentation.Comment: 12 Pages, 11 Figures, Journa
Enhancing egocentric 3D pose estimation with third person views
© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-NDWe propose a novel approach to enhance the 3D body pose estimation of a person computed from videos captured from a single wearable camera. The main technical contribution consists of leveraging high-level features linking first- and third-views in a joint embedding space. To learn such embedding space we introduce First2Third-Pose, a new paired synchronized dataset of nearly 2000 videos depicting human activities captured from both first- and third-view perspectives. We explicitly consider spatial- and motion-domain features, combined using a semi-Siamese architecture trained in a self-supervised fashion. Experimental results demonstrate that the joint multi-view embedded space learned with our dataset is useful to extract discriminatory features from arbitrary single-view egocentric videos, with no need to perform any sort of domain adaptation or knowledge of camera parameters. An extensive evalu- ation demonstrates that we achieve significant improvement in egocentric 3D body pose estimation per- formance on two unconstrained datasets, over three supervised state-of-the-art approaches. The collected dataset and pre-trained model are available for research purposes.This work has been partially supported by projects PID2020-120 049RB-I00 and PID2019-110977GA-I00 funded by MCIN/ AEI/10.13039/501100 011033 and by the âEuropean Union NextGener-ationEU/PRTRâ, as well as by grant RYC-2017-22563 funded by MCIN/ AEI /10.13039/501100 011033 and by âESF Investing in your futureâ, and network RED2018-102511-T funded by MCIN/ AEIPeer ReviewedPostprint (published version
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