VCD: A Video Conferencing Dataset for Video Compression

TL;DR

The paper introduces VCD, a new dataset tailored for evaluating video codecs in video conferencing, capturing diverse qualities and scenarios to improve compression efficiency assessment.

Contribution

VCD is the first dataset specifically designed for video conferencing scenarios, including diverse qualities and background processing, enabling better codec evaluation and tuning.

Findings

Compression efficiency varies significantly across scenarios.

Source quality impacts codec performance.

VCD provides a realistic benchmark for conferencing video codecs.

Abstract

Commonly used datasets for evaluating video codecs are all very high quality and not representative of video typically used in video conferencing scenarios. We present the Video Conferencing Dataset (VCD) for evaluating video codecs for real-time communication, the first such dataset focused on video conferencing. VCD includes a wide variety of camera qualities and spatial and temporal information. It includes both desktop and mobile scenarios and two types of video background processing. We report the compression efficiency of H.264, H.265, H.266, and AV1 in low-delay settings on VCD and compare it with the non-video conferencing datasets UVC, MLC-JVC, and HEVC. The results show the source quality and the scenarios have a significant effect on the compression efficiency of all the codecs. VCD enables the evaluation and tuning of codecs for this important scenario. The VCD is publicly available as an open-source dataset at https://github.com/microsoft/VCD.