期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B5
页码：7-12
出版社：Copernicus Publications
摘要：We present a method for 3D reconstruction of industrial sites using a combination of images and point clouds with a motivation of achieving higher levels of automation, precision, and reliability. Recent advances in 3D scanning technologies have made possible rapid and cost-effective acquisition of dense point clouds for 3D reconstruction. As the point clouds provide explicit 3D information, they have a much higher potential for the automation of reconstruction. However, due to the measurement principle employed by laser scanners and their limited point density, the information on sharp edges is not very reliable. It is precisely where images have superiority over point clouds. In addition images are required for visual interpretation, texture mapping, and modelling parts not visible in the point clouds. Moreover, image acquisition is more flexible, and the cost and time required for it is much lower than that of laser scanning, making their combined use essential for a cost-effective solution. These reasons led us to develop a modelling strategy that uses both images and point clouds in combination with a library of CAD primitives found in industrial scenarios represented as CSG (Constructive Solid Geometry) objects. The modelling pipeline in our algorithm starts from point clouds as the main data source for automation. First of all we segment the point cloud using surface smoothness and detect simple objects like planes and cylinders using Hough Transform. This is followed by fitting of CSG objects to a combination of segments. These fitted CAD models are used as registration targets for adding more scans to the project. Additionally, by fitting the projected edges to image gradients we register images to point clouds. Once we have a registered data set, manual measurements are added to images to model missing parts and to increase the reliability of modelling for portions where laser data is known to be noisy. The final phase is similar to bundle adjustment in traditional Photogrammetry as there we estimate pose and shape parameters of all CSG objects using all image measurements and points clouds simultaneously. We name this final phase Integrated Adjustment as it integrates all available information to determine the unknown parameters. The results of applying this method to data from an industrial site are presented showing the complementary nature of point cloud and image data. An analysis of improvement in quality of 3D reconstruction shows the benefits of the adopted approach
