Self-localization method for three-dimensional handy scanner using multi spot laser

Kumiko Yoshida, K. Kawasue
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引用次数: 1

Abstract

On the computer vision system, if the shape of the object includes complex parts, unmeasurable area exists for occlusions of the part on its surface in many cases. The area where camera can observe in a frame is also limited and the limitation causes the unmeasurable area. In order to reduce the unmeasurable area, scanning the measurement device is required. Many numbers of views of each model from different position (orientation) have to be taken to reconstruct the whole shape of the model. The point cloud data (surface data) obtained by the measurement device are connected to reconstruct the model. The connection of the data is performed by considering the movement of the measurement system (Self-localization) or using ICP (Iterative Closest Point) algorithm. Accuracy of the connection influences the result of the model reconstructions. Reliable and accurate self-localization of measurement device is introduced in this paper.
多光斑激光三维手持扫描仪的自定位方法
在计算机视觉系统中,如果物体的形状包含复杂的零件,很多情况下,零件在其表面存在不可测量的遮挡面积。摄像机在一个画面中所能观察到的区域也是有限的,这种限制导致了不可测量的区域。为了减少不可测量的面积,需要对测量装置进行扫描。为了重建模型的整体形状,必须从不同的位置(方向)对每个模型进行大量的视图。将测量装置获得的点云数据(曲面数据)连接起来重建模型。通过考虑测量系统的运动(自定位)或使用ICP(迭代最近点)算法来实现数据的连接。连接的准确性直接影响模型重建的结果。介绍了测量装置的可靠、精确的自定位方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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