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3D surface reconstruction based on Kinect

机译:基于Kinect的3D表面重建

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摘要

In this paper, a simple and efficient 3D surface reconstruction algorithm which can be implemented on mid or low-end computers is proposed. In this algorithm, the 3D images are obtained by a depth motion sensing device named Kinect. Data from region of interests are obtained by segmenting images whose k-neighbor relationship is established with a k-dimensional tree (KD-tree). After patching the point cloud holes with a bicubic spline function and a triangular mesh, the 3D surface of the object is reconstructed. Furthermore, the neighborhoods defined differently are used to connect regions since several non-connected regions exist in the point cloud. Experimental results show that the proposed algorithm based on the Kinect platform can be used to reconstruct complete and smooth surface even if the point cloud is non-connected in space and some of the captured data are lost.
机译:本文提出了一种简单高效的3D表面重建算法,其可以在中间或低端计算机上实现。在该算法中,3D图像通过名为Kinect的深度运动感测装置获得。来自感兴趣区域的数据是通过用K维树(KD-Tree)建立k邻居关系的图像来获得的数据。在用双方样条函数和三角网格修补点云孔之后,重建对象的3D表面。此外,不同地定义的邻域用于连接区域,因为点云中存在几个非连接区域。实验结果表明,即使点云在空间中未连接,也可以使用基于Kinect平台的所提出的算法来重建完整和平滑的表面,并且一些捕获的数据丢失了一些捕获的数据。

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