3D modelling of archaeological small finds by the structure sensor range camera: comparison of different scanning applications
Today, range cameras represent a cheap, intuitive and effective technology for collecting the 3D geometry of objects and environments automatically and practically in real time. Such features can make these sensors a valuable tool for documenting archaeological small finds, especially when not expert users are involved. Therefore, in this work, Scanner and itSeez3D, two of the most promising scanning applications actually available for the Structure Sensor, a range camera specifically designed for mobile devices, were tested in order to evaluate their accuracy in modelling the 3D geometry of two archaeological artefacts, characterized by different shape and dimensions. The 3D models obtained through the two scanning applications were thus compared with the reference ones generated with the more accurate photogrammetric technique. The results demonstrate that both the applications show the same level of geometric accuracy, which amounts generally to very few millimetres, from an overall point of view, and, at the same time, they substantially point out the good quality of the Structure Sensor 3D reconstruction technology. In particular, the itSeez3D application is surely the best solution for the color restitution, even if it requires a payment of $7 to export and thus to use effectively each model generated. On the other side, Scanner is a free application and its geometric accuracy is comparable to that of itSeez3D, but, however, the colours are frequently smoothed and sometimes not fully rendered.
KeywordsRange camera Occipital structure sensorTM 3D modelling Software comparison Small finds
The authors are deeply indebted to the Superintendence of Trapani (R. Giglio) and the G. Whitaker Foundation (Palermo; M.P. Toti), for making available the two archaeological items.
This work was supported by the Sapienza University of Rome Archaeological Expedition to Motya under the funding “Grandi Scavi” of the University of Rome La Sapienza.
- Agisoft PhotoScan (2017). http://www.agisoft.com/
- Agisoft PhotoScan (2018) Agisoft PhotoScan User Manual. http://www.agisoft.com/pdf/photoscan-pro_1_4_en.pdf
- Bradski G, Kaehler A (2008) Learning openCV: computer vision with the openCV library. O’Reilly Media, Inc, SebastopolGoogle Scholar
- Ciasca A (1979) Scavi alle mura di mozia (campagna 1978). Rivista di Studi Fenici Roma 7(2):207–227Google Scholar
- Ciasca A, Toti MP (1994) Maschera. Scavi a Mozia: le terrecotte figurate, 33Google Scholar
- Girardeau-Montaut D (2017a) Cloud-to-mesh distance—CloudCompareWiki. http://www.cloudcompare.org/doc/wiki/index.php?title=Cloud-to-Mesh_Distance
- Girardeau-Montaut D (2017b) CloudCompare—3D point cloud and mesh processing software—Version 2.8.1. Open Source ProjectGoogle Scholar
- Itseez3D (2017). https://itseez3d.com/
- Orsingher A (2014) Listen and protect: reconsidering the grinning masks after a recent find from motya. Vicino Oriente 43:145–71Google Scholar
- Ravanelli R, Di Rita M, Nascetti A, Crespi M, Nigro L, Montanari D, Spagnoli F (2017a) Penguin 3.0—Capturing small finds in 3D. Mediterranean Archaeology and Archaeometry 17(2):49–56Google Scholar
- Ravanelli R, Lastilla L, Crespi M (2017b) 3D modelling by low-cost range camera: software evaluation and comparison. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W8:209–212Google Scholar
- Ravanelli R, Nascetti A, Di Rita M, Nigro L, Montanari D, Spagnoli F, Crespi M (2017c) 3D modelling of archaeological small finds by a low-cost range camera: methodology and first results. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-5/W1:589–592Google Scholar