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Algorithms for Multi-sensor and Multi-primitive Photogrammetric Triangulation

机译:多传感器和多原始摄影测量三角剖分的算法

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The steady evolution of mapping technology is leading to an increasing availability of multi-sensory geo-spatial datasets, such as data acquired by single-head frame cameras, multi-head frame cameras, line cameras, and light detection and ranging systems, at a reasonable cost. The complementary nature of the data collected by these systems makes their integration to obtain a complete description of the object space. However, such integration is only possible after accurate co-registration of the collected data to a common reference frame. The registration can be carried out reliably through a triangulation procedure which considers the characteristics of the involved data. This paper introduces algorithms for a multi-primitive and multi-sensory triangulation environment, which is geared towards taking advantage of the complementary characteristics of spatial data available from the above mentioned sensors. The triangulation procedure ensures the alignment of involved data to a common reference frame. The devised methodologies are tested and proven efficient through experiments using real multi-sensory data.
机译:制图技术的稳步发展导致越来越多的感官地理空间数据集的可用性,例如单头相机,多头相机,线相机以及光检测和测距系统采集的数据。合理的费用。这些系统收集的数据的互补性质使得它们可以集成以获得对对象空间的完整描述。但是,只有在将收集到的数据正确地共配准到共同的参考系之后,才能进行这种集成。可以通过考虑相关数据特征的三角测量程序可靠地进行注册。本文介绍了一种用于多基元和多传感器三角测量环境的算法,该算法旨在利用上述传感器提供的空间数据的互补特性。三角剖分过程可确保将相关数据与公共参考系对齐。通过使用真实的多感官数据进行的实验,对所设计的方法进行了测试并证明是有效的。

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