3D surface reconstruction based on Kinect

C. Chen, W. Zou, Jiajun Wang
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引用次数: 4

Abstract

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.
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基于Kinect的三维表面重建
本文提出了一种简单、高效、可在中低端计算机上实现的三维曲面重建算法。在该算法中,三维图像是由深度运动传感设备Kinect获得的。通过k维树(KD-tree)建立图像的k邻关系,对图像进行分割,得到感兴趣区域的数据。利用双三次样条函数和三角网格对点云孔进行修补后,重建物体的三维表面。此外,由于点云中存在多个非连通区域,因此使用不同定义的邻域来连接区域。实验结果表明,该算法在Kinect平台上,即使点云在空间上不连通,且部分捕获数据丢失,也能重建完整光滑的表面。
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