Context-aware point cloud streaming for high-fidelity holographic telepresence

Abstract Real-time holographic communication enables immersive remote interaction by transmitting dynamic three-dimensional representations of users and environments, providing a stronger sense of presence than conventional video conferencing. However, the high data throughput requirements of volumetric streaming introduce challenges related to bandwidth variability and heterogeneous device capabilities. This paper presents an end-to-end system for scalable, real-time holographic telepresence, designed to operate within a fixed volumetric data transmission budget. The proposed approach combines importance-driven and semantic-aware filtering to preserve perceptually and interaction-critical details, while degrading less relevant data. We also leverage gesture recognition to automatically identify and emphasize points of interest, enhancing interactivity and realism. Experimental results demonstrate high visual fidelity and responsive performance with low bandwidth requirements, enabling efficient holographic communication for diverse use cases across different platforms.