2023/03/07 by Kaiyuan Hu, Hu, Kaiyuan, Yili Jin +7 · 2 citations
Computer Science · Earth and Planetary Sciences · Engineering · #3D Shape Modeling and Analysis #3D Surveying and Cultural Heritage #Computer Graphics and Visualization Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Multimedia (cs.MM) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2303.03599
openalex publication_date 2023/03/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Recent years have witnessed a rapid development of immersive multimedia which bridges the gap between the real world and virtual space. Volumetric videos, as an emerging representative 3D video paradigm that empowers extended reality, stand out to provide unprecedented immersive and interactive video watching experience. Despite the tremendous potential, the research towards 3D volumetric video is still in its infancy, relying on sufficient and complete datasets for further exploration. However, existing related volumetric video datasets mostly only include a single object, lacking details about the scene and the interaction between them. In this paper, we focus on the current most widely used data format, point cloud, and for the first time release a full-scene volumetric video dataset that includes multiple people and their daily activities interacting with the external environments. Comprehensive dataset description and analysis are conducted, with potential usage of this dataset. The dataset and additional tools can be accessed via the following website: https://cuhksz-inml.github.io/fullscenevolumetricvideodataset/.