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Flying laser range sensor for large-scale site-modeling and its applications in Bayon digital archival projectl

机译:用于大型站点建模的飞行激光测距传感器及其在Bayon数字档案项目中的应用

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We have been conducting a project to digitize the Bayon temple, located at the center of Angkor-Thom in the kingdom of Cambodia. This is a huge structure, more than 150 meters long on all sides and up to 45 meters high. Digitizing such a large-scale object in fine detail requires developing new types of sensors for obtaining data of various kinds related to irregular positions such as the very high parts of the structure occluded from the ground. In this article, we present a sensing system with a moving platform, referred to as the Flying Laser Range Sensor (FLRS), for obtaining data related to these high structures from above them. The FLRS, suspended beneath a balloon, can be maneuvered freely in the sky and can measure structures invisible from the ground. The obtained data, however, has some distortion due to the movement of the sensor during the scanning process. In order to remedy this issue, we have developed several new rectification algorithms for the FLRS. One method is an extension of the 3D alignment algorithm to estimate not only rotation and translation but also motion parameters. This algorithm compares range data of overlapping regions from ground-based sensors and our FLRS. Another method accurately estimates the FLRS's position by combining range data and image sequences from a video camera mounted on the FLRS. We evaluate these algorithms using a IS-based method and verify that both methods achieve much higher accuracy than previous methods.
机译:我们一直在进行一个项目,以数字化位于柬埔寨王国吴哥城中心的巴戎寺。这是一个巨大的结构,四边长超过150米,最高可达45米。对这样的大型物体进行详细的数字化处理需要开发新型的传感器,以获取与不规则位置有关的各种数据,这些不规则位置例如是被地面遮挡的结构的非常高的部分。在本文中,我们介绍了一种带有移动平台的传感系统,称为飞行激光距离传感器(FLRS),用于从上方获取与这些高结构有关的数据。悬挂在气球下方的FLRS可以在天空中自由操纵,并且可以测量从地面看不见的结构。但是,由于传感器在扫描过程中的移动,所获得的数据会有些失真。为了解决这个问题,我们为FLRS开发了几种新的整流算法。一种方法是3D对齐算法的扩展,不仅可以估计旋转和平移,还可以估计运动参数。该算法比较了来自地面传感器和FLRS的重叠区域的距离数据。另一种方法是通过组合距离数据和安装在FLRS上的摄像机的图像序列来准确估算FLRS的位置。我们使用基于IS的方法评估这些算法,并验证这两种方法均比以前的方法具有更高的准确性。

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