Real-time 3D hand shape estimation based on inverse kinematics and physical constraints
Real-time 3D hand shape estimation based on inverse kinematics and physical constraints
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DOI：
10.1007/11553595_104
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发表时间：
2005-01-01
期刊：
影响因子：
--
通讯作者：
Taniguchi, R
中科院分区：
文献类型：
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作者：
Fujiki, R;Arita, D;Taniguchi, R
我们正在研究实时手形估计，我们将其应用于用户界面和交互式应用程序。我们采用了计算机视觉方法，因为无线传感提供了无限制的观察，或者说是一种自然的传感方式。问题在于，由于人手有很多关节，因此具有很高的几何自由度，这使得手部形状估计变得困难。例如，我们要处理自遮挡问题和大量计算。同时，人手具有多种物理约束，即每个关节都有可移动范围和相互依赖性，这可能会减少手形估计的搜索空间。本文提出了一种利用从相机图像获取的形状特征和启发式引入的物理手部约束来实时估计 3D 手部形状的新方法。我们在不复杂的背景下使用多个相机进行了初步实验。我们展示实验结果以验证我们提出的方法的有效性。
We are researching for real-time hand shape estimation, which we are going to apply to user interface and interactive applications. We have employed a computer vision approach, since unwired sensing provides restriction-free observation, or a natural way of sensing. The problem is that since a human hand has many joints, it has geometrically high degrees of freedom, which makes hand shape estimation difficult. For example, we have to deal with a self-occlusion problem and a large amount of computation. At the same time, a human hand has several physical constraints, i.e., each joint has a movable range and interdependence, which can potentially reduce the search space of hand shape estimation. This paper proposes a novel method to estimate 3D hand shapes in real-time by using shape features acquired from camera images and physical hand constraints heuristically introduced. We have made preliminary experiments using multiple cameras under uncomplicated background. We show experimental results in order to verify the effectiveness of our proposed method.