Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W8, 213-220, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W8-213-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
14 Nov 2017
CAPTURING FINE DETAILS INVOLVING LOW-COST SENSORS –A COMPARATIVE STUDY
N. Rehany, A. Barsi, and T. Lovas Department of Photogrammetry and Geoinformatics, Budapest University of Technology and Economics, Budapest, Hungary
Keywords: Laser scanning, object scanning, amateur sensors, low-cost sensors, comparison Abstract. Capturing the fine details on the surface of small objects is a real challenge to many conventional surveying methods. Our paper discusses the investigation of several data acquisition technologies, such as arm scanner, structured light scanner, terrestrial laser scanner, object line-scanner, DSLR camera, and mobile phone camera. A palm-sized embossed sculpture reproduction was used as a test object; it has been surveyed by all the instruments. The result point clouds and meshes were then analyzed, using the arm scanner’s dataset as reference. In addition to general statistics, the results have been evaluated based both on 3D deviation maps and 2D deviation graphs; the latter allows even more accurate analysis of the characteristics of the different data acquisition approaches. Additionally, own-developed local minimum maps were created that nicely visualize the potential level of detail provided by the applied technologies. Besides the usual geometric assessment, the paper discusses the different resource needs (cost, time, expertise) of the discussed techniques. Our results proved that even amateur sensors operated by amateur users can provide high quality datasets that enable engineering analysis. Based on the results, the paper contains an outlook to potential future investigations in this field.
Conference paper (PDF, 2949 KB)


Citation: Rehany, N., Barsi, A., and Lovas, T.: CAPTURING FINE DETAILS INVOLVING LOW-COST SENSORS –A COMPARATIVE STUDY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W8, 213-220, https://doi.org/10.5194/isprs-archives-XLII-2-W8-213-2017, 2017.

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