UVG-CWI-DQPC
Dual-Quality Point Cloud Dataset for Volumetric Video Applications
Guillaume Gautier (Tampere University)
Xuemei Zhou (TU Delft - Multimedia Computing, Centrum Wiskunde & Informatica (CWI))
Thong Nguyen (Tampere University)
Jack Jansen (Centrum Wiskunde & Informatica (CWI))
Louis Fréneau (Tampere University)
Marko Viitanen (Tampere University)
Uyen Phan (Tampere University)
Jani Käpylä (Tampere University)
Pablo Cesar (Centrum Wiskunde & Informatica (CWI), TU Delft - Multimedia Computing)
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Abstract
Volumetric video is a key enabler of immersive extended reality (XR) experiences and is often represented using point clouds for their structural simplicity. However, capturing volumetric content through multi-view acquisition and depth sensing poses many challenges, such as occlusions and depth mismatches. To foster research in this field, we introduce a unique dual-quality point cloud dataset, named UVG-CWI-DQPC, which is designed to support the development of point cloud enhancement, compression, and quality assessment. Our dataset includes 12 dynamic sequences captured simultaneously by: 1) a high-end capture system producing high-fidelity point clouds with extensive processing; and 2) a consumer-grade capture system relying on affordable RGB-D cameras, lightweight processing, and open-source tools. For each sequence, our dataset provides ground-truth point clouds from the high-end capture system and raw RGB-D footage from the consumer-grade capture system, along with calibration data and tools for point cloud generation. This dual-quality setup enables direct comparison and benchmarking of algorithms for densification, occlusion removal, registration, and quality enhancement. Our dataset is publicly available under a permissive license to support reproducible research and standardization work in Moving Picture Experts Group (MPEG) and 3rd Generation Partnership Project (3GPP).
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