活动简介
The success of AI machine learning in deep neural networks has led to substantial improvements in computer vision, speech recognition, natural language processing, and other applications at comparable human performance and beyond. The advancement of computer graphics, modeling, and simulation with innovative smart interactive devices energizes the acceleration of immersive computing in the marketplace.
Integrating AI machine learning and immersive computing can propel future Intelligent Reality (IR), providing real-time intelligent assistant user experience for the immersive environment. Also, to make machine learning inferencing more robust with realistic content rendering, leveraging big data for handling Volume and Velocity of data from a single source or Varieties of data from multiple sources would provide the IR the perfect playing field.
Overall, by anchoring these technologies and others being developed such as augmented reality (AR), virtual reality (VR), mixed reality (MR), extended reality (XR), and Digital Twins, the line between the physical world and the digital world with analytics capability will be increasingly less distinct.
This conference aims to foster the IR vision by understanding current best practices, future innovations, and standards development for how effective and efficient deploy AI machine learning and deep learning to the immersive environment (VR, AR, MR, and XR). The integration of smart interactive devices, immersive computing, and AI machine learning can transform and enhance learning and human performance in education, science, engineering, telemedicine, healthcare, manufacturing, finance, business, public services, and ultimately our society itself.
Sponsor Type:6
组委会
General Chair:
Wo Chang, NIST, US
Organization Chair:
Sin-Kuen Hawkins, IEEE, US
Technical Chair:
Kyoungro Yoo, Konkuk University, Korea
Competition Chair:
Louis Nisiotis (Chair), University. of Central Lancashire, Cyprus
Sang Kyun Kim (Co-Chair), Myoungil University., Korea
Publication Chair:
Elizabeth Chang, University of Maryland, US
征稿信息
重要日期
With the advancement of smart interactive devices, immersive technologies, and artificial intelligence (AI) algorithms, integrating these technologies can propel future Intelligent Reality (IR). Utilizing innovative technology, such as sensors, immersive computing, and AI machine learning, can provide real-time decision-making user experience with analytics capability within the immersive space. By leveraging these technologies and others being developed for augmented reality (AR), virtual reality (VR), mixed reality (MR), extended reality (XR), and Digital Twins, the line between the physical world and the digital world with intelligent assistant capability will be increasingly less distinct.
The formation of these technologies can transform and enhance learning and human performance in education, science, engineering, telemedicine, healthcare, manufacturing, finance, business, public services, and ultimately our society itself.
The first IEEE International Conference on Intelligent Reality explores real-time analytics capability by integrating and deploying AI machine learning into immersive (VR, AR, MR, and XR) space. It provides a forum to encourage the exchange of ideas with leading researchers and industry professionals in this intersection.
征稿范围
We invite researchers, industries, and standards experts to submit their work on this new frontier of Intelligent Reality. Areas of interest include but are not limited to:
1. Intelligent Reality Science and Foundations
Advanced Analytical Models
Efficient neural network inference Engines, Transfer Learning
Innovative Rendering Models
Security, Privacy, Integrity, and Ethics
Evaluation Metrics and Methodologies
Novel Quality Models
Quality of Experience
New Standards
2. Intelligent Reality Technology and Infrastructure
Neural Network Compression
Point Cloud Compression
Immersive Visual Media: Omidirectional, 360, 3DoF, 3DoF, 6DoF+, etc.
Spatial Audio, 3D Surround Sounds
Geometric Modeling and Design
Media Coded Representation
Interact Machine Learning between Virtual Objects and Real World
Interoperability between Machine Learning, Virtual Objects, and Real World
Sensor Fusion
Visual Analytics
Multimodel Interaction and Experience
Rendering Techniques
System Architectures, Design, and Deployment
Energy-efficient Computing
New Programming Models and Environments
Software Techniques and Architectures
3. Hardware, Accelerators, Devices for Intelligent Reality
AR Glasses, VR Headsets, other AR/VR Form-Factors, Smart Devices
Sensors technology in actuators, tactile, haptic, etc. for IR applications
Network on Chip, System on Chip, Programmable Chip
FPGA/CGRA/GPU/etc. accelerators for IR applications
Operating system support and runtimes for hardware accelerators
Programming models and platforms for accelerators
Novel system organizations and designs
Computation in memory/storage/network
4. Intelligent Reality Applications
Arts, Games, Leisure, Sports, and Entertainment
E-commerce, Retail, Real Estate
3D Model and Terrain Data
Interior Design, Landscaping & Urban Planning
Tourism and Travel
Telepresence, Teleoperation, collaboration, and social interactions
Education, Simulation, and Training
Healthcare, Medicine, Therapy
Transportation, Automotive, Aerospace
Geospatial
Finance
Industrial, Military, Emergency Response
Communication and Collaboration
Manufacturing and Occupational Safety
Advertising & Marketing
Government, Public Sector and Society in General
5. Intelligent Reality Services
Emergency
Environmental
Public Safety
Health Care
Public Transportation
Travel and Booking
Public Buildings
Repair & Maintenance
Social
Urban Planning
Professional
Housing
Tourism
6. Intelligent Reality Management
Content Creation, Authoring, and Management
Analytics Services and Management
Scalability and Efficiency between AI, Virtual Objects, and Real World
Data Acquisition, Integration, Cleaning, and Best Practices
Visualization Analytics
Computational Modeling and Data Integration
7. Security, Ethics, Privacy, and Trust in Intelligent Reality
Research in Security, Privacy, Integrity, and Ethics
Techniques and Models for Fairness, Diversity, Transparency, and Interpretability
Experimental Studies of Fairness, Diversity, Accountability, and Transparency
User Impacts of Novel Attacks
Trade-offs between Transparency and Privacy
Intrusion, Anomaly, Threat Detection
Multi-layer Defensive Frameworks
Novel Threats, Attacks, Mitigations
Trust Management
8. Social Connection and Concerns in Intelligent Reality
User Behaviors and Psychology
Groups and Communities Interaction
User Safety for in Social Environments
全部留言
重要日期
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会议日期
05月12日
2021
至05月14日
2021
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03月01日 2021
初稿截稿日期
-
03月29日 2021
初稿录用通知日期
-
05月14日 2021
注册截止日期
留言