Abstract
Abstract. 3D point clouds, acquired by state-of-the-art terrestrial laser scanning techniques (TLS), provide spatial information about accuracies up to several millimetres. Unfortunately, common TLS data has no spectral information about the covered scene. However, the matching of TLS data with images is important for monoplotting purposes and point cloud colouration. Well-established methods solve this issue by matching of close range images and point cloud data by fitting optical camera systems on top of laser scanners or rather using ground control points. The approach addressed in this paper aims for the matching of 2D image and 3D point cloud data from a freely moving camera within an environment covered by a large 3D point cloud, e.g. a 3D city model. The key advantage of the free movement affects augmented reality applications or real time measurements. Therefore, a so-called real image, captured by a smartphone camera, has to be matched with a so-called synthetic image which consists of reverse projected 3D point cloud data to a synthetic projection centre whose exterior orientation parameters match the parameters of the image, assuming an ideal distortion free camera.
Highlights
Conventional approaches for the registration of images and point clouds use the combination of optical systems and laser scanners or tie points
With the aid of modern smartphones, it is possible to measure the exterior orientation from smartphone-taken images using inbuilt Micro-Electronic-Measurement-Systems (MEMS) for orientation and Global Navigation Satellite Systems (GNSS) for position information
These information could be used for a reverse projection of 3D point cloud data which provides synthetic images of ordered 2D pixels with respectively additional exterior informaZtion about the mapped objects
Summary
Conventional approaches for the registration of images and point clouds use the combination of optical systems and laser scanners or tie points. With the aid of modern smartphones, it is possible to measure the exterior orientation from smartphone-taken images using inbuilt Micro-Electronic-Measurement-Systems (MEMS) for orientation and Global Navigation Satellite Systems (GNSS) for position information These information could be used for a reverse projection (hereafter referred to as re-projection) of 3D point cloud data which provides synthetic images of ordered 2D pixels with respectively additional exterior informaZtion about the mapped objects. To deal with the issue, the registration of smartphone and synthetic images uses the 3D geometry information of the point cloud. To detect falsely background information inside foreground objects, resulting from this noise, a pyramid approach is used It can be simplified described as inflating the re-projected points to create continuous image areas which are used for noise reduction and to provide homogeneous image areas. A resolution of about 3 MP is used which is a compromise in the level of detail and lower resolution respecting the synthetic images
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