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Remarks on a real-time 3D human body posture estimation method using trinocular images

机译:关于使用三曲图像的实时3D人体姿势估算方法的备注

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This paper proposes a new real-time method of estimating human postures in 3D form trinocular images. The proposed method extracts feature points of the human body by applying a type of function analysis to contours of human silhouettes. To overcome self-occlusion problems, dynamic compensation is carried out using the Kalman filter and all feature points are tracked. The 3D coordinates of the feature points are reconstructed by considering the geometrical relationship between the three cameras. Experimental results confirm both the feasibility and the effectiveness of the proposed method, and an application example of the 3D human body posture estimation to a motion recognition system is presented.
机译:本文提出了一种估算3D形式三曲图像中人姿势的新实时方法。所提出的方法通过将一种功能分析应用于人体轮廓的轮廓来提取人体的特征点。为了克服自闭锁问题,使用卡尔曼滤波器进行动态补偿,并跟踪所有特征点。通过考虑三个摄像机之间的几何关系,重建特征点的3D坐标。实验结果证实了所提出的方法的可行性和有效性,并提出了对运动识别系统的3D人体姿势估计的应用示例。

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