Hierarchical Optimization of 3D Point Cloud Registration
نویسندگان
چکیده
منابع مشابه
Cloud To Cloud Registration For 3d Point Data
Grant, Darion Shawn. Ph.D., Purdue University, December 2013. Cloud To Cloud Registration For 3D Point Data. Major Professors: James Bethel and Melba Crawford. The vast potential of digital representation of objects by large collections of 3D points is being recognized on a global scale and has given rise to the popularity of point cloud data (PCD). 3D imaging sensors provide a means for quickl...
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Point cloud registration is an inevitable problem in many applications, such as modelling in large scale outdoor environment with the point cloud captured by the moving scanner. How to put these point cloud into the same coordinate system fast and efficiently is the bottleneck to accomplish the 3D modeling applications. In this paper, we propose a new approach which cans register point clouds a...
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In order to construct survey-grade 3D models of buildings, roads, railway stations, canals and other similar structures, the 3D environment must be fully recorded with accuracy. Following this, accurate measurements of the dimensions can be made on the recorded 3D datasets to enable 3D model extraction without having to return to the site and in significantly reduced times. The model may be com...
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A point cloud registration method based on 3D lines extraction from 3D data to register point cloud with obvious edges is proposed in this paper. Firstly, the line feature point cloud (LFPC), which is corresponding to the objects' edges, is extracted from the measured 3D data by using surface curvature as a measure. Then, through applying the 3D Hough transformation on LFPC, the line directions...
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ژورنال
عنوان ژورنال: Sensors
سال: 2020
ISSN: 1424-8220
DOI: 10.3390/s20236999