An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing
Dimitrios S. Alexiadis, Anargyros Chatzitofis, Nikolaos Zioulis, Olga, Zoidi, Georgios Louizis, Dimitrios Zarpalas, and Petros Daras

TL;DR
This paper presents an integrated platform for real-time 3D human reconstruction and motion capture using multiple RGB-D sensors, featuring novel calibration, reconstruction, and evaluation methods validated on multi-Kinect2 datasets.
Contribution
It introduces a comprehensive system combining novel calibration, a GPU-accelerated reconstruction algorithm, and a new evaluation framework for real-time 3D human capture.
Findings
Validated on multi-Kinect2 datasets
Achieved robust and fast 3D reconstruction
Demonstrated accurate skeleton tracking
Abstract
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…
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