Real-time, immersive telecommunication systems are quickly becoming a reality, thanks to the advances in acquisition, transmission, and rendering technologies. Point clouds in particular serve as a promising representation in these type of systems, offering photorealistic rendering capabilities with low complexity. Further development of transmission, coding, and quality evaluation algorithms, though, is currently hindered by the lack of publicly available datasets that represent realistic scenarios of remote communication between people in real-time. In this paper, we release a dynamic point cloud dataset that depicts humans interacting in social XR settings. Using commodity hardware, we capture a total of 45 unique sequences, according to several use cases for social XR. As part of our release, we provide annotated raw material, resulting point cloud sequences, and an auxiliary software toolbox to acquire, process, encode, and visualize data, suitable for real-time applications. The dataset can be accessed via the following link:

, , ,
MMSys '21: 12th ACM Multimedia Systems Conference
Distributed and Interactive Systems

Reimat, I, Alexiou, E, Jansen, A.J, Viola, I, Subramanyam, S, & César Garcia, P.S. (2021). CWIPC-SXR: Point cloud dynamic human dataset for Social XR. In Proceedings of the ACM Multimedia Systems Conference (pp. 300–306). doi:10.1145/3458305.3478452