论文标题
手动引导的表达和分割估计
A Hand Motion-guided Articulation and Segmentation Estimation
论文作者
论文摘要
在本文中，我们提出了一种使用人手运动在RGB-D图像中同时发音模型估计和分割的方法。我们的方法在初始发音模型估计，基于ICP的模型参数优化和目标对象的区域选择的过程中使用手运动。手运动对铰接模型进行了初步猜测：棱柱形或革命接头。该方法通过将RGB-D图像与手动运动的约束对齐来估算关节参数。最后，目标区域是从群集区域中选择的，这些区域与关节模型对称移动。我们的实验结果表明，各种对象提出的方法的鲁棒性。
In this paper, we present a method for simultaneous articulation model estimation and segmentation of an articulated object in RGB-D images using human hand motion. Our method uses the hand motion in the processes of the initial articulation model estimation, ICP-based model parameter optimization, and region selection of the target object. The hand motion gives an initial guess of the articulation model: prismatic or revolute joint. The method estimates the joint parameters by aligning the RGB-D images with the constraint of the hand motion. Finally, the target regions are selected from the cluster regions which move symmetrically along with the articulation model. Our experimental results show the robustness of the proposed method for the various objects.
