An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing
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Abstract (arXiv)
The latest developments in 3D capturing, processing, and rendering provide means to unlock novel 3D application pathways. The main elements of an integrated platform, which target tele-immersion and future 3D applications, are described in this paper, addressing the tasks of real-time capturing, robust 3D human shape/appearance reconstruction, and skeleton-based motion tracking. More specifically, initially, the details of a multiple RGB-depth (RGB-D) capturing system are given, along with a novel sensors' calibration method. A robust, fast reconstruction method from multiple RGB-D streams is then proposed, based on an enhanced variation of the volumetric Fourier transform-based method, parallelized on the Graphics Processing Unit, and accompanied with an appropriate texture-mapping algorithm. On top of that, given the lack of relevant objective evaluation methods, a novel framework is proposed for the quantitative evaluation of real-time 3D reconstruction systems. Finally, a generic, multiple depth stream-based method for accurate real-time human skeleton tracking is proposed. Detailed experimental results with multi-Kinect2 data sets verify the validity of our arguments and the effectiveness of the proposed system and methodologies.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Dec 2017.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 4; 2025: 2; 2026: 3.
12 papers.
- 2021HUMAN4D: A Human-Centric Multimodal Dataset for Motions and Immersive Mediacited by 29
- 2023High-Quality Animatable Dynamic Garment Reconstruction from Monocular Videoscited by 5
- 2024Headset: Human emotion awareness under partial occlusions multimodal datasetcited by 4
- 2026SHOW3D: Capturing Scenes of 3D Hands and Objects in the Wildcited by 4
- 2024OMEGAS: Object Mesh Extraction from Large Scenes Guided by Gaussian Segmentationcited by 3
- 2024Simultaneously Recovering Multi-Person Meshes and Multi-View Cameras with Human Semanticscited by 3
- 2025YOWO: You Only Walk Once to Jointly Map An Indoor Scene and Register Ceiling-mounted Camerascited by 1
- 2021DeepMoCap: Deep Optical Motion Capture Using Multiple Depth Sensors and Retro-Reflectorscited by 0
- 2024GMFL-Net: A Global Multi-geometric Feature Learning Network for Repetitive Action Countingcited by 0
- 2025Ego-Exo 3D Hand Tracking in the Wild with a Mobile Multi-Camera Rigcited by 0
- 2026DynaTok: Token-Based 4D Reconstruction from Partial Point Cloudscited by 0
- 2026Human4K: A Large-Scale 4K Multi-View Mocap Dataset for Whole-Body 3D Human Reconstructioncited by 0
- 2026Human4K: A Large-Scale 4K Multi-View Mocap Dataset for Whole-Body 3D Human Reconstruction15 Jul 2026
- 2026DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds10 Jun 2026
- 2026SHOW3D: Capturing Scenes of 3D Hands and Objects in the Wild30 Mar 2026
- 2025YOWO: You Only Walk Once to Jointly Map An Indoor Scene and Register Ceiling-mounted Cameras20 Nov 2025
- 2025Ego-Exo 3D Hand Tracking in the Wild with a Mobile Multi-Camera Rig2 Oct 2025
- 2024Simultaneously Recovering Multi-Person Meshes and Multi-View Cameras with Human Semantics25 Dec 2024
- 2024GMFL-Net: A Global Multi-geometric Feature Learning Network for Repetitive Action Counting31 Aug 2024
- 2024OMEGAS: Object Mesh Extraction from Large Scenes Guided by Gaussian Segmentation24 Apr 2024
- 2024Headset: Human emotion awareness under partial occlusions multimodal dataset14 Feb 2024
- 2023High-Quality Animatable Dynamic Garment Reconstruction from Monocular Videos2 Nov 2023
- 2021DeepMoCap: Deep Optical Motion Capture Using Multiple Depth Sensors and Retro-Reflectors14 Oct 2021
- 2021HUMAN4D: A Human-Centric Multimodal Dataset for Motions and Immersive Media14 Oct 2021