MagicStream: Bandwidth-conserving Immersive Telepresence via Semantic Communication

Immersive telepresence has the potential to revolutionize remote communication by offering a highly interactive and engaging user experience. However, state-of-the-art exchanges large volumes of 3D content to achieve satisfactory visual quality, resulting in substantial Internet bandwidth consumption. To tackle this challenge, we introduce MagicStream, a first-of-its-kind semantic-driven immersive telepresence system that effectively extracts and delivers compact semantic details of captured 3D representation of users, instead of traditional bit-by-bit communication of raw content. To minimize bandwidth consumption while maintaining low end-to-end latency and high visual quality, MagicStream incorporates the following key innovations: (1) efficient extraction of user's skin/cloth color and motion semantics based on lighting characteristics and body keypoints, respectively; (2) novel, real-time human body reconstruction from motion semantics; and (3) on-the-fly neural rendering of users' immersive representation with color semantics. We implement a prototype of MagicStream and extensively evaluate its performance through both controlled experiments and user trials. Our results show that, compared to existing schemes, MagicStream can drastically reduce Internet bandwidth usage by up to 1195X while maintaining good visual quality.

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Publication Details

Published
2024-11-04
DOI
https://doi.org/10.1145/3666025.3699344
Citations
14
Primary Topic
Image and Video Quality Assessment
Type
article
Field-Weighted Citation Impact
3.49
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article

MagicStream: Bandwidth-conserving Immersive Telepresence via Semantic Communication

Ruizhi Cheng, Nan Wu, Bo Han, Eugene Chai et al.
14 citations
Image and Video Quality Assessment
3.49
article

MagicStream: Bandwidth-conserving Immersive Telepresence via Semantic Communication

Ruizhi Cheng, Nan Wu, Bo Han, Eugene Chai, Matteo Varvello, Vu Le
article en
14 citations

Abstract

Immersive telepresence has the potential to revolutionize remote communication by offering a highly interactive and engaging user experience. However, state-of-the-art exchanges large volumes of 3D content to achieve satisfactory visual quality, resulting in substantial Internet bandwidth consumption. To tackle this challenge, we introduce MagicStream, a first-of-its-kind semantic-driven immersive telepresence system that effectively extracts and delivers compact semantic details of captured 3D representation of users, instead of traditional bit-by-bit communication of raw content. To minimize bandwidth consumption while maintaining low end-to-end latency and high visual quality, MagicStream incorporates the following key innovations: (1) efficient extraction of user's skin/cloth color and motion semantics based on lighting characteristics and body keypoints, respectively; (2) novel, real-time human body reconstruction from motion semantics; and (3) on-the-fly neural rendering of users' immersive representation with color semantics. We implement a prototype of MagicStream and extensively evaluate its performance through both controlled experiments and user trials. Our results show that, compared to existing schemes, MagicStream can drastically reduce Internet bandwidth usage by up to 1195X while maintaining good visual quality.

George Mason University (US), University of Massachusetts Amherst (US), Nokia (United States) (US)
Reduced inequalities
Openalex Percentile: Top 6%
Image and Video Quality Assessment
3.49
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