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Building Facade Point Clouds Segmentation Based on Optimal Dual-Scale Feature Descriptors
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作者 Zijian Zhang Jicang Wu 《Journal of Computer and Communications》 2024年第6期226-245,共20页
To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-sca... To address the current issues of inaccurate segmentation and the limited applicability of segmentation methods for building facades in point clouds, we propose a facade segmentation algorithm based on optimal dual-scale feature descriptors. First, we select the optimal dual-scale descriptors from a range of feature descriptors. Next, we segment the facade according to the threshold value of the chosen optimal dual-scale descriptors. Finally, we use RANSAC (Random Sample Consensus) to fit the segmented surface and optimize the fitting result. Experimental results show that, compared to commonly used facade segmentation algorithms, the proposed method yields more accurate segmentation results, providing a robust data foundation for subsequent 3D model reconstruction of buildings. 展开更多
关键词 3D Laser scanning point clouds Building Facade Segmentation point cloud Processing Feature Descriptors
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Application of 3D Digital Modeling Technology in the Construction of Digital Cities
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作者 Xuke Wang 《Journal of Geographic Information System》 2023年第1期98-109,共12页
The concepts of “digital twins”, “3D real scene”, “metacosm” and others were the technical paths for building digital cities with the development of emerging surveying and mapping science and technology, which w... The concepts of “digital twins”, “3D real scene”, “metacosm” and others were the technical paths for building digital cities with the development of emerging surveying and mapping science and technology, which was to build a digital and virtualized city that matched the real physical world, to achieve a one-to-one correspondence between all elements of the physical world and the digital virtual world. And one of its basic geographic information data was a highly similar, virtual simulation of the 3D real scene. After exploring the traditional manual 3DsMax modeling, UAV low-altitude digital oblique photogrammetry modeling, airborne laser scanning modeling and other single modeling technologies, this paper discussed the 3D digital modeling technology used by the UAV airborne laser scanning point cloud and low-altitude digital oblique photogrammetry for complementary integration, constructing the 3D scene of the digital city. This paper expounded the technical route and production process of 3D digital modeling, in order to provide technical references for related projects. 展开更多
关键词 Airborne Laser scanning point clouds Low-Altitude Oblique Photogrammetry Real Scenes Digital City Digital Twins
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An Algorithm to Recognize the Target Object Contour Based on 2D Point Clouds by Laser-CCD-Scanning 被引量:1
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作者 MAO Hongyong SHI Duanwei +4 位作者 ZHOU Ji XU Pan CHEN Shiyu XU Yuxiang FENG Fan 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2015年第4期355-361,共7页
For a vision measurement system consisted of laser-CCD scanning sensors, an algorithm is proposed to extract and recognize the target object contour. Firstly, the two-dimensional(2D) point cloud that is output by th... For a vision measurement system consisted of laser-CCD scanning sensors, an algorithm is proposed to extract and recognize the target object contour. Firstly, the two-dimensional(2D) point cloud that is output by the integrated laser sensor is transformed into a binary image. Secondly, the potential target object contours are segmented and extracted based on the connected domain labeling and adaptive corner detection. Then, the target object contour is recognized by improved Hu invariant moments and BP neural network classifier. Finally, we extract the point data of the target object contour through the reverse transformation from a binary image to a 2D point cloud. The experimental results show that the average recognition rate is 98.5% and the average recognition time is 0.18 s per frame. This algorithm realizes the real-time tracking of the target object in the complex background and the condition of multi-moving objects. 展开更多
关键词 laser-CCD scanning sensor 2D point cloud contour recognition improved Hu invariant moments BP neural network
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