Abstract
In the field of cultural heritage, operators make use of high resolution orthophotos of paintings both for purposes related to restoration and monitoring of art pieces and for realizing online documentations and exhibitions. Unfortunately, artworks to be restored and/or presented in digital museums are painted on canvas which are far to be perfectly planar. Therefore, technical documentation accompanying an artwork to be stored in digital archives or museums can be enriched by information related to the 3D shape of the canvas. In this paper, both the design of a portable low-cost device that allows the acquisition of the 3D geometry of the painting and a procedure to triangulate 3D data are proposed. Such a procedure, working using the principle of laser-camera triangulation, is based on the use of a set of fiducial markers to set and continuously control the reciprocal orientation of the laser source and of the camera.
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References
Vassilopoulou, S., Hurni, L., Dietrich, V., Baltsavias, E., Pateraki, M., Lagios, E., Parcharidis, I.: Orthophoto generation using IKONOS imagery and high-resolution DEM: a case study on volcanic hazard monitoring of Nisyros Island (Greece). ISPRS J. Photogramm. Remote Sens. 57, 24–38 (2002). https://doi.org/10.1016/S0924-2716(02)00126-0
Jacobsen, K., Passini, R.: Accuracy of digital orthophotos from high resolution space imagery. In: Proceedings of the Workshop High Resolution Mapping from Space (2003)
Gros, P.: How to use the cross ratio to compute 3D invariants from two images how to use the cross ratio to compute projective invariants from two images? (1994). https://doi.org/10.1007/3-540-58240-1_6
Mohr, R., Gravir, B.T.: Projective geometry for image analysis (1996)
Remondino, F., Rizzi, A., Barazzetti, L., Scaioni, M., Fassi, F., Brumana, R., Pelagotti, A.: Review of geometric and radiometric analyses of paintings. Photogramm. Rec. 26, 439–461 (2011). https://doi.org/10.1111/j.1477-9730.2011.00664.x
Liverani, A., Leali, F., Pellicciari, M.: Real-time 3D features reconstruction through monocular vision. Int. J. Interact. Des. Manuf. 4, 103–112 (2010). https://doi.org/10.1007/s12008-010-0093-5
Volpe, Y., Furferi, R., Governi, L., Tennirelli, G.: Computer-based methodologies for semi-automatic 3D model generation from paintings. Int. J. Comput. Aided Eng. Technol. 6, 88 (2014). https://doi.org/10.1504/IJCAET.2014.058012
Barazzetti, L., Remondino, F., Scaioni, M., Lo Brutto, M., Rizzi, A., Brumana, R.: Geometric and radiometric analysis of paintings, pp. 62–67 (2010)
Bimber, O., Coriand, F., Kleppe, A., Bruns, E., Zollmann, S., Langlotz, T.: Superimposing pictorial artwork with projected imagery. In: ACM SIGGRAPH 2006 Courses on - SIGGRAPH 2006, p. 10. ACM Press, New York (2006). https://doi.org/10.1145/1185657.1185805
Governi, L., Carfagni, M., Furferi, R., Puggelli, L., Volpe, Y.: Digital bas-relief design: a novel shape from shading-based method. Comput. Aided. Des. Appl. 11, 153–164 (2014). https://doi.org/10.1080/16864360.2014.846073
Rosten, E., Drummond, T.: Machine learning for high-speed corner detection (2006). https://doi.org/10.1007/11744023_34
Santachiara, M., Gherardini, F., Leali, F.: An augmented reality application for the visualization and the pattern analysis of a Roman mosaic. IOP Conf. Ser. Mater. Sci. Eng. 364, 012094 (2018). https://doi.org/10.1088/1757-899X/364/1/012094
Köhler, J., Pagani, A., Stricker, D.: Detection and identification techniques for markers used in computer vision. In: VLUDS 2010 - Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop) (2010). https://doi.org/10.4230/OASIcs.VLUDS.2010.36
An, G., Lee, S., Seo, M.-W., Yun, K., Cheong, W.-S., Kang, S.-J., An, G.H., Lee, S., Seo, M.-W., Yun, K., Cheong, W.-S., Kang, S.-J.: Charuco board-based omnidirectional camera calibration method. Electronics 7, 421 (2018). https://doi.org/10.3390/electronics7120421
Garrido-Jurado, S., Muñoz-Salinas, R., Madrid-Cuevas, F.J., Marín-Jiménez, M.J.: Automatic generation and detection of highly reliable fiducial markers under occlusion. Pattern Recogn. 47, 2280–2292 (2014). https://doi.org/10.1016/j.patcog.2014.01.005
Furferi, R., Governi, L., Volpe, Y., Carfagni, M.: Design and assessment of a machine vision system for automatic vehicle wheel alignment. Int. J. Adv. Robot. Syst. 10, 242 (2013). https://doi.org/10.5772/55928
Vosselman, G., Gorte, B.G.H., Sithole, G., Rabbani, T.: Recognising structure in laser scanning point clouds (2004). https://research.utwente.nl/en/publications/recognising-structure-in-laser-scanning-point-clouds
Scaramuzza, D., Harati, A., Siegwart, R.: Extrinsic self calibration of a camera and a 3D laser range finder from natural scenes. In: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4164–4169. IEEE (2007). https://doi.org/10.1109/IROS.2007.4399276
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Puggelli, L., Furferi, R., Governi, L. (2020). Low Cost Device to Perform 3D Acquisitions Based on ChAruCo Markers. In: Rizzi, C., Andrisano, A.O., Leali, F., Gherardini, F., Pini, F., Vergnano, A. (eds) Design Tools and Methods in Industrial Engineering. ADM 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-31154-4_17
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