Our Work “SemNFT: A Semantically Enhanced Decentralized Middleware for Digital Asset Immortality” Is Accepted By ACM MM’24

Non-Fungible Tokens (NFTs) have emerged as a pivotal digital asset, offering authenticated ownership of unique digital content. Despite it has gained remarkable traction, yet face pressing storage and verification challenges stemming from blockchain’s permanent data costs. Existing off-chain or centralized storage solutions, while being alternatives, also introduce notable security vulnerabilities. We present SemNFT, an innovative decentralized framework integrated with blockchain oracle middleware services, addressing these persistent NFT dilemmas.

Continue Reading

Our Work “Web3 Metaverse: State-of-the-Art and Vision” Is Accepted By ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)

The metaverse, as a rapidly evolving socio-technical phenomenon, exhibits significant potential across diverse domains by leveraging Web3 (a.k.a. Web 3.0) technologies such as blockchain, smart contracts, and non-fungible tokens (NFTs). This survey aims to provide a comprehensive overview of the Web3 metaverse from a human-centered perspective. We systematically review the metaverse’s industrial (data from Dow Jones Factiva database) and academic (data from Google Scholar website) developments over the past 30 years, highlighting the balanced contributions from its core components: Web3, immersive convergence, and crowd intelligence communities.

Continue Reading

Our Work “MetaCast: A Self-Driven Metaverse Announcer Architecture Based on Quality of Experience Evaluation Model” Is Accepted By ACM MM’ 23

We propose a three-stage architecture for metaverse announcers, which is designed to identify events, position cameras, and blend between shots. Based on the architecture, we introduce a Metaverse Announcer User Experience (MAUE) model to identify the factors affecting the users’ Quality of Experience (QoE) from a human-centered perspective. In addition, we implement MetaCast, a practical self-driven metaverse announcer in a university campus metaverse prototype, to conduct user studies for MAUE model. The experimental results have effectively achieved satisfactory announcer settings that align with the preferences of most users, encompassing parameters such as video transition rate, repetition rate, importance threshold value, and image composition.

Continue Reading