基于双层层次聚类模型的运动学逆解

Xiaoyue Liu, Hui-Yi Liu, Jie Gao
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引用次数: 0

摘要

本文提出了一种基于双层分层聚类模型的运动学逆解。它将人体骨骼分成若干块,建立了一个双层分层聚类模型。基于BVH格式运动捕捉数据中关节端点位置与角度向量的关系,利用K-MEANS聚类方法将关节端点位置向量聚类,然后利用最近邻聚类方法将每个关节的角度向量聚类。在此基础上,以坐标系间一致性为约束条件,进行了运动学逆解。实验结果表明,该方法具有精度高、求解速度快、适应性强等特点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Inverse Kinematic Solution Based on a Two-Layer Hierarchical Cluster Model
This paper proposes an inverse kinematics solution based on a two-layer hierarchical cluster model. It divides a human skeleton into blocks to build a two-layer hierarchical cluster model. Based on the relationship between the end position and angle vectors of joints in the BVH format motion capture data as well as to make the end position vectors of joints into clusters with the K-MEANS cluster method, we then make the angle vectors of each joint into clusters with the nearest-neighbor cluster method. Based on that, the inverse kinematics solution is made with the consistency between frames as the constraint condition. The experiment results show that the method is high accuracy, fast solution speed and strong adaptability.
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