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单目视频中人体三维运动的迭代优化估计

3D Human Motion Reconstruction from Monocular Videos through Iterative Optimization

  • 摘要: 提出并实现了一种从单目视频流中重建人体三维运动的方法.该方法通过交互定制得到个性化的人体骨架模型和视频序列每一帧中人体各关节点的二维坐标后,分别针对单帧和连续多帧进行优化并迭代求解,得到每一帧的比例因子的最优解;最后反求各关节点的三维坐标,重建人体三维运动序列.对包含复杂和快速多变的人体运动的视频进行的实验表明,该方法简单有效,适用于包括体育、影视等在内的实际视频源.

     

    Abstract: A novel approach on reconstruction of 3D motion of a human figure from a monocular video is proposed. By the method, a human stick model and the 2D feature points of each frame are obtained manually. The scale factor is computed and optimized in each frame. In the solution, an iterative optimization algorithm for a series of subsequence is also proposed to obtain the optimum solution. Finally, the 3D coordinates of each joint is computed to reconstruct the sequence of 3D human motion. Experiments on challenging videos including complex and highly dynamic motions show the effectiveness of the approach. This approach can be applied to real videos such as sports, movies and so on.

     

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