Demo: Benchmarking and Visualizing Compression Errors in Volumetric Streaming Systems

Volumetric streaming is a powerful medium that transmits volumetric data, which primarily includes color and depth information, over a network in real-time. While color data can be effectively compressed using standard video codecs, compressing depth data poses a significant challenge as we need to change the bitrate for transmission over standard video codecs. Streaming depth data using standard video codecs introduces visual artifacts that degrade the quality of volumetric streaming workflows. To address this issue, we propose a demonstration exploring efficient compression techniques for color and depth data that minimize visual artifacts while preserving visual fidelity. Using a physical tabletop game filmed with volumetric cameras, we compare two voumetric streaming video workflows. The first workflow streams and renders the color and depth data directly from the camera in an uncompressed format, which is used as the ground truth. The second workflow encodes and streams the data in a compressed format. The comparison is conducted on a desktop system to evaluate performance for analyzing factors such as data transmission, compression quality, and overall system responsiveness.