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A Multiple Camera System with Real-Time Volume Reconstruction for Articulated Skeleton Pose Tracking

机译:具有实时体积重构的多摄像机系统,用于关节骨骼姿势跟踪。

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We present a multi-camera system for recovering skeleton body pose, by performing real-time volume reconstruction and using a hierarchical stochastic pose search algorithm. Different from many multi-camera systems that require a few connected workstations, our system only uses a signle PC to control 8 cameras for synchronous image acquisition. Silhouettes of the 8 cameras are extracted via a color-based background subtraction algorithm, and set as input to the 3D volume reconstruction. Our system can perform real-time volume reconstruction rendered in point clouds, voxels as well as voxels with texturing. The full-body skeleton pose (29-D vector) is then recovered by fitting an articulated body model to the volume sequences. The pose estimation is performed in a hierarchical manner, by using a particle swarm opt-mization (PSO) based search strategy combined with soft constraints. 3D distance transform (DT) is used for reducing the computing time of objective evaluations.
机译:我们提出了一种通过执行实时体积重建并使用分层随机姿势搜索算法来恢复骨架姿势的多相机系统。与许多需要几个连接的工作站的多摄像机系统不同,我们的系统仅使用一台智能PC来控制8个摄像机以进行同步图像采集。通过基于颜色的背景减除算法提取8个摄像机的轮廓,并将其设置为3D体积重建的输入。我们的系统可以执行在点云,体素以及带有纹理的体素中渲染的实时体积重建。然后,通过将关节运动的人体模型拟合到体序列,来恢复全身骨架姿势(29-D矢量)。通过使用结合了软约束的基于粒子群优化(PSO)的搜索策略,以分层方式执行姿态估计。 3D距离变换(DT)用于减少客观评估的计算时间。

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