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VOXEL BASED ANNEALED PARTICLE FILTERING FOR MARKERLESS 3D ARTICULATED MOTION CAPTURE

机译:基于体素的无标记3D铰接运动捕获的退火颗粒滤波

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This paper presents a view-independent approach to markerless human motion capture in low resolution sequences from multiple calibrated and synchronized cameras. Redundancy among cameras is exploited to generate a 3D voxelized representation of the scene and a human body model (HBM) is introduced towards analyzing these data. An annealed particle filtering scheme where every particle encodes an instance of the pose of the HBM is employed. Likelihood between particles and input data is performed using occupancy and surface information and kinematic constrains are imposed in the propagation step towards avoiding impossible poses. Test over the HumanEva annotated dataset yield quantitative results showing the effectiveness of the proposed algorithm.
机译:本文提出了一种独立于多个校准和同步摄像机的低分辨率序列中无标记人体运动捕获的视图的方法。利用相机之间的冗余以产生场景的3D体蛋白化表示,并引入人体模型(HBM)朝向分析这些数据。一种退火的颗粒滤波方案,其中每个粒子编码HBM的姿势的实例。使用占用率和输入数据之间的可能性,并且使用占用和表面信息和运动学约束在传播步骤中施加到避免不可能的姿势。对人类注释的数据集产生定量结果,显示了所提出的算法的有效性。

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