Exploring the data of blockchain-based metaverses

In recent years the concept of metaverse has evolved in the attempt of defining richer immersive and interactive environments supporting various types of virtual experiences and interactions among users. This has led to the emergence of various different metaverse platforms that utilize blockchain technology and non-fungible tokens (NFTs) to establish ownership of metaverse elements and attach features and information to it. This article will delve into the heterogeneity of the data involved in these metaverse platforms, as well as highlight some dynamics and features of them. Moreover, the paper introduces a metaverse analysis tool developed by the authors, which leverages machine learning techniques to collect and analyze daily data, including blockchain transactions, platform-specific metadata, and social media trends. Experimental results are reported are presented with a use-case scenario focused on the trading of digital parcels, commonly referred to as metaverse real estate.Comment: In Proceedings of the IEEE International Conference on Metaverse Computing, Networking and Applications (IEEE METACOM 2023), June 26--28, 2023, Japa

MPAI-EEV: Standardization Efforts of Artificial Intelligence based End-to-End Video Coding

The rapid advancement of artificial intelligence (AI) technology has led to the prioritization of standardizing the processing, coding, and transmission of video using neural networks. To address this priority area, the Moving Picture, Audio, and Data Coding by Artificial Intelligence (MPAI) group is developing a suite of standards called MPAI-EEV for "end-to-end optimized neural video coding." The aim of this AI-based video standard project is to compress the number of bits required to represent high-fidelity video data by utilizing data-trained neural coding technologies. This approach is not constrained by how data coding has traditionally been applied in the context of a hybrid framework. This paper presents an overview of recent and ongoing standardization efforts in this area and highlights the key technologies and design philosophy of EEV. It also provides a comparison and report on some primary efforts such as the coding efficiency of the reference model. Additionally, it discusses emerging activities such as learned Unmanned-Aerial-Vehicles (UAVs) video coding which are currently planned, under development, or in the exploration phase. With a focus on UAV video signals, this paper addresses the current status of these preliminary efforts. It also indicates development timelines, summarizes the main technical details, and provides pointers to further points of reference. The exploration experiment shows that the EEV model performs better than the state-of-the-art video coding standard H.266/VVC in terms of perceptual evaluation metric

The MPEG Representation of Digital Media

More and more information, audio and video but also a range of other information type, is generated, processed and used by machines today, even though the end user may be a human. The result over the past 15 years has been a substantial increase in the type of information and change in the way humans generate, classify, store, search, access and consume information. Conversion of information to digital form is a prerequisite for this enhanced machine role, but must be done having in mind requirements such as compactness, fidelity, interpretability etc.  This book provides an overview of the basic technology and mechanisms underpinning the operation of MPEG standards. It is a valuable reference for those making decisions in products and services based on digital media, those with general background, engaged in studies or developments of MPEG-related implementations, and those curious about MPEG and its role in the development of successful, standard technologies. Offers an overview of what’s behind MP3, digital television, online movies and why these innovations changed the world; Provides a comprehensive treatment of all aspects of signal digitization; Presents not only the state-of-the-art, but also what are the drivers of what is coming next and what is developing in key R&D labs; Provides examples of new human sense experiences for all sorts of users and new business opportunities these offer

Digital Rights Management: le ragioni del sì e le ragioni del no

2008-04-10T Hotel, Via dei Giudicati, CagliariContenuti Digitali: Audio, Video, Musica e Tecnologi

Exploring blockchain-based metaverses: Data collection and valuation of virtual lands using machine learning techniques

In recent years, the concept of the metaverse has evolved significantly, with the aim of defining richer immersive and interactive environments that can support various types of virtual experiences and interactions among users. This evolution has given rise to several metaverse platforms that utilize blockchain technology and non-fungible tokens (NFTs) to establish ownership of metaverse elements and attach features and information to them. This article seeks to delve into the complexity and heterogeneity of the data involved in these metaverse platforms and highlight some of the dynamics and features that make them unique. Additionally, the paper introduces a metaverse analysis tool developed by the authors, which leverages machine learning techniques to collect and analyze daily data, including blockchain transactions, platform-specific metadata, and social media trends. The experimental results of our approach are presented with a use-case scenario focused on the trading of digital parcels, commonly referred to as metaverse real estate. This scenario allows us to demonstrate the effectiveness of our tool and showcase the potential of using machine learning techniques to analyze and gain insights into the metaverse ecosystem

An MPAI/IEEE International Standard for Audio: Overview of CAE Audio Recording Preservation (ARP) Technology

The Audio Recording Preservation (ARP) technology represents a significant development in the field of audio preservation and is an essential component of the Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI) Context-based Audio Enhancement (CAE) standard. This standard has been adopted by the IEEE Standard Association as IEEE 3302-2022 and it specifies a range of AI-based technologies for various audio applications, including communication, entertainment, post-production, teleconferencing, and preservation. This article aims to highlight the specific contribution of CAE-ARP technology to audio preservation applications. The CAE-ARP technology has several innovative features that make it a valuable tool in the digitization and preservation of open-reel audio tapes. It leverages automated AI for extracting relevant information from digitized audio files and for creating preservation and access copies. By using the ARP standard, archives can effectively manage all the information stored onto tapes, along with related metadata, to automatically prepare the content for storage and/or immediate use. This technology represents a significant advancement in the field of audio preservation and provides an effective solution for managing small and large collections of open-reel audio tapes

AI-based media coding and beyond

MPAI-Moving Picture, Audio and Data Coding by Artificial Intelligence is the first body developing data coding standards that have Artificial Intelligence (AI) as its core technology. MPAI believes that universally accessible standards for AI-based data coding can have the same positive effects on AI as standards had on digital media. Elementary components of MPAI standards-AI Modules (AIM)-expose standard interfaces for operation in a standard AI Framework (AIF). As their performance may depend on the technologies used, MPAI expects that competing developers providing AIMs will promote horizontal markets of AI solutions that build on and further promote AI innovation. Finally, the MPAI Framework Licences provide guidelines to IPR holders facilitating the availability of compatible licences to standard users