纹理自旋图像的3D配准

N. Brusco, M. Andreetto, A. Giorgi, G. Cortelazzo
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引用次数: 52

摘要

这项工作的动机是利用当前距离相机通常与距离数据相关的光度信息进行3D配准。自动配对3D配准过程分为两步,第一步对刚性运动参数进行自动粗略估计,第二步通过ICP算法或其变体对其进行细化。如何有效地实现首次原油自动估计仍然是一个开放的研究领域。旋转图像是一种非常有效的3D匹配技术。由于旋转图像仅利用几何信息,因此很自然地扩展其原始定义以包含纹理信息。这样的操作显然可以通过多种方式进行。本文介绍了自旋图像的一种特殊扩展,称为纹理自旋图像,并演示了其在3D配准中的性能。我们将看到,纹理自旋图像具有非凡的特性,因为它们可以提供比标准自旋图像更鲁棒、更精确、更抗噪声的刚性运动估计,而且计算成本更低。
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3D registration by textured spin-images
This work is motivated by the desire of exploiting for 3D registration purposes the photometric information current range cameras typically associate to range data. Automatic pairwise 3D registration procedures are two steps procedures with the first step performing an automatic crude estimate of the rigid motion parameters and the second step refining them by the ICP algorithm or some of its variations. Methods for efficiently implementing the first crude automatic estimate are still an open research area. Spin-images are a 3D matching technique very effective in this task. Since spin-images solely exploit geometry information it appears natural to extend their original definition to include texture information. Such an operation can clearly be made in many ways. This work introduces one particular extension of spin-images, called textured spin-images, and demonstrates its performance for 3D registration. It will be seen that textured spin-images enjoy remarkable properties since they can give rigid motion estimates more robust, more precise, more resilient to noise than standard spin-images at a lower computational cost.
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