Real-time 3D reconstruction and pose estimation for human motion analysis

In this paper, we present a markerless 3D motion capture system based on a volume reconstruction technique of non rigid bodies. It depicts a new approach for pose estimation in order to fit an articulated body model into the captured real-time information. We aim at analyzing athlete's movements in real-time within a 3D interactive graphics system. The paper addresses recent trends in vision based analysis and its fusion with 3D interactive computer graphics. Hence, the proposed system presents new methods for the 3D reconstruction of human body parts from calibrated multiple cameras based on voxel carving techniques and a 3D pose estimation methodology using Pseudo-Zernike Moments applied to an articulated human body model. Several algorithms have been designed for the deployment within a GPGPU environment allowing us to calculate several principle process steps from segmentation and reconstruction to volume optimization in real-time.