Finding Articulated Body in Time-Series Volume Data
Finding Articulated Body in Time-Series Volume Data
复制标题
在时间序列体积数据中查找铰接体
DOI：
10.1007/11789239_41
复制
发表时间：
2006
期刊：
影响因子：
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通讯作者：
T. Matsuyama
中科院分区：
文献类型：
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作者：
T. Mukasa;S. Nobuhara;A. Maki;T. Matsuyama
本文提出了一种从时间序列体数据中获取三维运动学结构和运动的新方案，特别是针对人体。我们的基本策略是首先通过使用aMRG，增强的多分辨率Reeb图[6]来表示每个帧中目标的形状结构，然后对每个形状结构进行变形，以便在整个输入帧中将所有形状结构识别为共同的运动学结构。虽然帧与帧之间的形状结构可能非常不同，但我们建议通过聚类图的一些节点来导出唯一的运动学结构，这是基于它们是部分相干的事实。我们所做的唯一假设是，人体可以近似为具有一定数量的端点和分支的关节体。我们通过一些实验证明了所提出的方案的有效性。
This paper presents a new scheme for acquiring 3D kinematic structure and motion from time-series volume data, in particular, focusing on human body. Our basic strategy is to first represent the shape structure of the target in each frame by using aMRG, augmented Multiresolution Reeb Graph [6], and then deform each of the shape structures so that all of them can be identified as a common kinematic structure throughout the input frames. Although the shape structures can be very different from frame to frame, we propose to derive a unique kinematic structure by way of clustering some nodes of graph, based on the fact that they are partly coherent. The only assumption we make is that human body can be approximated by an articulated body with certain number of end-points and branches. We demonstrate the efficacy of the proposed scheme through some experiments.