Abstract
The paper presents triangulation-based accuracy test procedures for PhotoScan 3D modelling software with automatic features including camera station identification, point cloud construction and the generation of polygon networks and polygon net textures. The process starts with establishing the camera resolutions. Then, internal orientation elements of the cameras are established by means of different calibration techniques and comparisons between them are made. 3D models are then tested using diverse model generation parameters and different configurations of sets of images including how each type of calibration affects the resulting 3D model accuracy. To conclude, 3D model accuracy is compared with geodesic surveying results.
Highlights
Internal orientation elements of the cameras are established by means of different calibration techniques and comparisons between them are made. 3D models are tested using diverse model generation parameters and different configurations of sets of images including how each type of calibration affects the resulting 3D model accuracy
The trend has recently been driven by sophisticated digital image processing algorithms as well as by 3D modelling of objects using specialized autocorrelation software
Relative comparisons of differently calibrated models were made by means of CloudCompare (Fig. 6) The results have shown that PhotoScan’s calibration ability is excellent to the point of making the use of specialised calibration software redundant
Summary
The science discipline of photogrammetry has been seeing a progressive development toward ever better techniques of precisely determining the dimensions of objects and terrain features from photographic images. Combined with the above developments, modern personal computers provide adequate computing power to enable efficient and reasonably accurate 3D modelling at reasonable cost. For another 3D modelling method see (Dandoš et al 2013). Digital photography is the single data source for 3D modelling This begs the question of how digital image quality affects the accuracy of a 3D model generated from it. The resulting image resolution value tells us how many pixels are stored in a data file produced by the camera and the lens. All available shutter and resolution setting combinations and both data formats were used to produce up to 128 images per camera. The output consists of the optimum shutter (f) and resolution setting combination for each camera, see Table 1
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