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A Comparative Study of Noise Elimination Algorithms for a 3D Terrain Model through Object Clustering and the Differential Method

机译:基于对象聚类和微分方法的3D地形模型噪声消除算法的比较研究

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摘要

The technology to automatically detect the surrounding working environment for modeling of the result is the key essential technique for the automation of the construction equipment developments. When noise takes place during 3D modeling of the front work area of the automated construction equipments, the point of noise occurrence during the surface modeling can result in ground level phenomenon in the form of triangular pyramid to lower the quality of the modeling. This can greatly affect the detection of the objects around the automated equipment. This study proposed revised object clustering and differential algorithms for noise elimination of 3D terrain model and compared the noise elimination performance of existing algorithm and proposed algorithm on the images of actual earthwork working environment. It is expected that the noise elimination algorithm proposed in this study will be very useful as a widely used essential technology required for the development of automated technology not only in earthwork field but also in other general construction and civil engineering fields by noise elimination of the 3D working environment model.
机译:自动检测周围工作环境以对结果进行建模的技术是建筑设备开发自动化的关键关键技术。当在自动化施工设备的前部工作区域进行3D建模时发生噪声时,在表面建模过程中出现的噪声点可能会导致三角形金字塔形式的地平面现象,从而降低建模质量。这会极大地影响对自动化设备周围物体的检测。该研究提出了改进的对象聚类和差分算法,用于消除3D地形模型的噪声,并比较了现有算法和提出的算法在实际土方工作环境图像上的噪声消除性能。可以预期,这项研究中提出的噪声消除算法作为广泛应用的基本技术将非常有用,这不仅是土方领域,而且在其他一般建筑和土木工程领域中通过3D噪声消除技术开发自动化技术所需的技术。工作环境模型。

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