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arXiv · 2405.14866

Tele-Aloha: A Low-budget and High-authenticity Telepresence System Using Sparse RGB Cameras

Hanzhang Tu·Ruizhi Shao·Xue Dong·Shunyuan Zheng·Hao Zhang·Lili Chen·Meili Wang·Wenyu Li·Siyan Ma·Shengping Zhang·Boyao Zhou·Yebin Liu
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Abstract

In this paper, we present a low-budget and high-authenticity bidirectional telepresence system, Tele-Aloha, targeting peer-to-peer communication scenarios. Compared to previous systems, Tele-Aloha utilizes only four sparse RGB cameras, one consumer-grade GPU, and one autostereoscopic screen to achieve high-resolution (2048x2048), real-time (30 fps), low-latency (less than 150ms) and robust distant communication. As the core of Tele-Aloha, we propose an efficient novel view synthesis algorithm for upper-body. Firstly, we design a cascaded disparity estimator for obtaining a robust geometry cue. Additionally a neural rasterizer via Gaussian Splatting is introduced to project latent features onto target view and to decode them into a reduced resolution. Further, given the high-quality captured data, we leverage weighted blending mechanism to refine the decoded image into the final resolution of 2K. Exploiting world-leading autostereoscopic display and low-latency iris tracking, users are able to experience a strong three-dimensional sense even without any wearable head-mounted display device. Altogether, our telepresence system demonstrates the sense of co-presence in real-life experiments, inspiring the next generation of communication.

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Hanzhang Tu, Ruizhi Shao, Xue Dong, Shunyuan Zheng, Hao Zhang, Lili Chen, Meili Wang, Wenyu Li, Siyan Ma, Shengping Zhang, Boyao Zhou, Yebin Liu. 2024-05-23. Tele-Aloha: A Low-budget and High-authenticity Telepresence System Using Sparse RGB Cameras. https://arxiv.org/abs/2405.14866

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