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

TL;DR

Tele-Aloha is a cost-effective, high-fidelity telepresence system that uses sparse RGB cameras and advanced view synthesis to enable realistic, low-latency 3D communication without head-mounted displays.

Contribution

The paper introduces a novel view synthesis algorithm and a complete low-budget telepresence system utilizing only four RGB cameras and a consumer GPU for high-quality 3D communication.

Findings

Achieves 2048x2048 resolution at 30 fps with less than 150ms latency.

Provides a strong 3D sense through autostereoscopic display and iris tracking.

Demonstrates effective peer-to-peer telepresence in real-life experiments.

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.