基于多视点几何的移动距离传感器三维数据校正

K. Kozuka, J. Sato
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引用次数: 2

摘要

对于大型物体的三维形状测量,移动距离传感器扫描是最有效的方法之一。然而,如果我们使用移动距离传感器,在扫描过程中,由于传感器的运动,所获得的数据会有一定的失真。在本文中,我们提出了一种利用多视图几何方法从移动距离传感器中恢复正确的三维距离数据的方法。我们假设距离传感器以光栅扫描顺序辐射激光束,并且从静态相机上观察激光束。我们首先证明了我们可以将距离数据作为三维时空图像来处理,并证明了扩展的多视图几何可以用来表示相机图像的三维时空与距离数据的三维时空之间的关系。接下来,我们证明了扩展投影下的多视图几何可以用于校正由移动距离传感器获得的三维数据。在合成图像和距离数据中对该方法进行了实现和测试。并对恢复的三维形状的稳定性进行了评价。
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Rectification of 3D Data Obtained from Moving Range Sensors by using Multiple View Geometry
For measuring the 3D shape of large objects, scanning by a moving range sensor is one of the most efficient method. However, if we use moving range sensors, the obtained data have some distortions due to the movement of the sensor during the scanning process. In this paper, we propose a method for recovering correct 3D range data from a moving range sensor by using the multiple view geometry. We assume that range sensor radiates laser beams in raster scan order, and they are observed from a static camera. We first show that we can deal with range data as 3D space-time images, and show that the extended multiple view geometry can be used for representing the relationship between the 3D space-time of camera image and the 3D space-time of range data. We next show that the multiple view geometry under extended projections can be used for rectifying 3D data obtained by the moving range sensor. The method is implemented and tested in synthetic images and range data. The stability of recovered 3D shape is also evaluated.
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