基于眼动追踪的聚焦压缩技术，三倍降带宽仍保沉浸感。
Foveated Compression for Immersive Telepresence Visualization
- 根据眼动数据动态调整视频编码量化参数，核心区域保质。
- 实验表明带宽可降至1/3，沉浸感无明显损失。
- 适用于远程操控与沉浸式视频，尤其适合眼动设备用户。
沉浸式远程可视化在远程存在和远程操作中至关重要，但常受通信带宽限制。本文提出一种轻量级的沉浸式远程可视化视频流聚焦压缩方法，可轻松集成至常见视频编码器中，当有眼动追踪数据时能显著降低所需带宽。具体而言，我们基于眼动信息自适应地调整现代块基视频编码器的量化参数，使中央视觉区域以高保真度传输，而周边区域质量降低，从而节省带宽。我们将该方法集成至赢得ANA Avatar XPRIZE竞赛的NimbRo人形机器人系统中。实验表明，带宽可降至三分之一，且沉浸感未受损。通过定性示例分析传输保真度，并报告定量结果。
原文摘要 · Abstract (English)
Immersive televisualization is important both for telepresence and teleoperation, but resolution and fidelity are often limited by communication bandwidth constraints. We propose a lightweight method for foveated compression of immersive televisualization video streams that can be easily integrated with common video codecs, reducing the required bandwidth if eye tracking data is available. Specifically, we show how to spatially adjust the Quantization Parameter of modern block-based video codecs in a adaptive way based on eye tracking information. The foveal region is transmitted with high fidelity while quality is reduced in the peripheral region, saving bandwidth. We integrate our method with the NimbRo avatar system, which won the ANA Avatar XPRIZE competition. Our experiments show that bandwidth can be reduced to a third without sacrificing immersion. We analyze transmission fidelity with qualitative examples and report quantitative results.
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