Task matching & scheduling algorithm of hybrid avator team in collaborative virtual environments

2008 ◽  
Author(s):  
Hui-Yi Liu ◽  
Jing-Fen Chen
Keyword(s):  
Virtual Environments ◽  
Scheduling Algorithm ◽  
Collaborative Virtual Environments

LIRKIS Global Collaborative Virtual Environments: Current State and Utilization Perspective

2020 ◽  
Vol 11 (1) ◽  
pp. 99-106
Author(s):  
Marián Hudák ◽  
Štefan Korečko ◽  
Branislav Sobota
Keyword(s):  
Virtual Reality ◽  
Virtual Environments ◽  
Smart Devices ◽  
Collaborative Virtual Environments ◽  
Web Based ◽  
Smart Client ◽  
Input Devices ◽  
User Input ◽  
History Of ◽  
Shared Virtual Environments

AbstractRecent advances in the field of web technologies, including the increasing support of virtual reality hardware, have allowed for shared virtual environments, reachable by just entering a URL in a browser. One contemporary solution that provides such a shared virtual reality is LIRKIS Global Collaborative Virtual Environments (LIRKIS G-CVE). It is a web-based software system, built on top of the A-Frame and Networked-Aframe frameworks. This paper describes LIRKIS G-CVE and introduces its two original components. The first one is the Smart-Client Interface, which turns smart devices, such as smartphones and tablets, into input devices. The advantage of this component over the standard way of user input is demonstrated by a series of experiments. The second component is the Enhanced Client Access layer, which provides access to positions and orientations of clients that share a virtual environment. The layer also stores a history of connected clients and provides limited control over the clients. The paper also outlines an ongoing experiment aimed at an evaluation of LIRKIS G-CVE in the area of virtual prototype testing.

Visualising and populating the Web: Collaborative virtual environments for browsing, searching and inhabiting Webspace

1997 ◽  
Vol 29 (15) ◽  
pp. 1751-1761 ◽  
Author(s):  
Steve Benford ◽  
Dave Snowdon ◽  
Chris Brown ◽  
Gail Reynard ◽  
Rob Ingram
Keyword(s):  
Virtual Environments ◽  
Collaborative Virtual Environments ◽  
The Web

Human interactions and personal space in collaborative virtual environments

2010 ◽  
Vol 14 (4) ◽  
pp. 229-240 ◽  
Author(s):  
Nasser Nassiri ◽  
Norman Powell ◽  
David Moore
Keyword(s):  
Virtual Environments ◽  
Personal Space ◽  
Collaborative Virtual Environments ◽  
Human Interactions

Educational Implications

2014 ◽  
pp. 361-388
Keyword(s):  
Online Learning ◽  
Social Networking ◽  
Virtual Environments ◽  
Second Life ◽  
Classroom Environment ◽  
Visual Presentation ◽  
Virtual Education ◽  
Collaborative Virtual Environments ◽  
Science Approach ◽  
Approach To Teaching

An integrative art-science approach to teaching is described, involving imaging concepts about science, with three approaches to integration of art and science: 1) visual presentation of scientific concepts, 2) creating art by finding inspiration in a science-based topic, 3) learning visually for other courses taken concurrently by arranging data into a structured whole. The next part of the chapter is about several dimensions that seem important in blended and online learning regarding social networking and the collaborative virtual environments. Virtual education in a first life and a Second Life classroom environment is discussed next.

Construction of Collaborative Virtual Environments

2005 ◽  
pp. 235-268 ◽  
Author(s):  
Anthony Steed ◽  
Emmanuel Frecon
Keyword(s):  
Virtual Environments ◽  
Data Sharing ◽  
Data Structures ◽  
Network Topology ◽  
Main Body ◽  
System Software ◽  
Collaborative Virtual Environments ◽  
Implementation Framework ◽  
Environment Model ◽  
The Common

In this chapter, we give an overview of some of the issues that face programmers and designers when building collaborative virtual environments (CVEs). We do this by highlighting three aspects of CVE system software: the environment model (data structures, behaviour description) that the system provides, the data-sharing mechanism (how the environment model is shared), and the implementation framework (the structure of a typical client or platform in terms of the services it provides to the user). When a CVE system is designed, choices have to be made for each of these aspects, and this then constrains how the designers and programmers go about constructing the CVE worlds themselves. We present the main body of the overview by using examples that highlight many of the important differences between CVE systems. We will also relate our discussion to the common topics of network topology and awareness management.

Automatic Approach to Evaluate Collaborative Interaction in Virtual Environments

2019 ◽  
pp. 1-23 ◽  
Author(s):  
Luis Casillas ◽  
Adriana Peña ◽  
Alfredo Gutierrez
Keyword(s):  
Virtual Environments ◽  
Virtual Space ◽  
Fuzzy Classification ◽  
Collaborative Virtual Environments ◽  
Rule Based ◽  
Layer Analysis ◽  
High Level ◽  
Task Oriented ◽  
Intelligent Tutor ◽  
Time Information

Virtual environments for multi-users, collaborative virtual environments (CVE), support geographical distant people to experience collaborative learning and team training. In this context, monitoring collaboration provides valuable, and in time, information regarding individual and group indicators, helpful for human instructors or intelligent tutor systems. CVE enable people to share a virtual space, interacting with an avatar, generating nonverbal behavior such as gaze-direction or deictic gestures, a potential means to understand collaboration. This chapter presents an automated model and its inference mechanisms to evaluate collaboration in CVE based on expert human rules of nonverbal participants' activity. The model is a multi-layer analysis that includes data filtering, fuzzy classification, and rule-based inference producing a high-level assessment of group collaboration. This approach was applied to a task-oriented session, where two participants assembled cubes in a CVE to create a figure.

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