Abstract
Anthropometry is an objective tool serving to evaluate the shape of the face and reveal changes observed in the subject over time, or among different subjects, analyzing quantitative and qualitative differences. It also permits the study of normal and abnormal growth, diagnosis of genetic or acquired malformations, planning and evaluation of surgical and/or orthodontic therapy, and verification of the treatment results by analyzing, measuring and comparing the face shape. Among 3D digitization technologies, photogrammetry shows great promise because it is a low cost, biocompatible, safe and non-invasive methodology, but it still suffers from a need for considerable human intervention. In previous research, the Authors illustrated a new approach based on a 3-Cameras photogrammetric system. After several tests, conducted to verify the validity of this methodology, the present experimental study was carried out using a re-engineered photogrammetric scanning system to obtain landmark-models of human faces, and comparing these results with those achieved with laser scanning, applied to a dummy face (in order to eliminate errors caused by breathing movements in a living subject). Two different, specifically designed experimental 3D photogrammetric setups have been developed and tested to enhance the performance. This research demonstrates the potential of low-cost photogrammetry for medical digitization; further research will be addressed to testing the use of the scanning system on humans to validate its clinical performance.
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References
D’Apuzzo, N. (2006). Overview of 3D surface digitization technologies in Europe, three-dimensional image capture and applications VI. In B.D. Corner, P. Li, M. Tocheri (Eds.), Proceedings of SPIE-IS&T Electronic Imaging, SPIE, vol. 6056. San Jose, CA, USA.
Bowyer, K.W., Chang, K., & Flynn, P. (2005). A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition. Computer Vision and Image Understanding, 101(1), 1–15.
Zhao, W., Chellappa, R., & Rosenfeld, A. (2003). Face recognition: A literature survey. ACM Computing Surveys, pp. 399–458.
Lane, C., & Harrell, W. (2008). Completing the 3-dimensional picture. American Journal of Orthodontics and Dentofacial Orthopedics, 133(4), 612–620.
Baik, H., Jeon, J., & Leeb, H. (2007). Facial soft-tissue analysis of Korean adults with normal occlusion using a 3-dimensional laser scanner. American Journal of Orthodontics and Dentofacial Orthopedics, 133(4), 612–620.
Stylianou, G., & Farin, G. (2004). Crest lines for surface segmentation and flattening. IEEE Transactions on Visualization and Computer Graphics, 10(5), 536–544.
Mangan, A., & Whitaker, R. (1999). Partitioning 3D surface meshes using watershed segmentation. IEEE Transactions on Visualization and Computer Graphics, 5(4).
Galantucci, L.M., Percoco, G., & Dal Maso, U. (2008). Coded targets and hybrid grids for photogrammetric 3D digitisation of human faces. Virtual and Physical Prototyping, 3(3 ISSN), 1745–2759.
Ferrandes, R., Galantucci, L., & Percoco, G. (2004). Optical methods for reverse engineering of human faces. 4th International CIRP 2004 Design Seminar. 16–18 May 2004, Session 6B, pp. 1–12 Cairo, Egypt.
Di Gioia, E., Deli, R., Galantucci, L.M., & Percoco, G. (2008). Reverse Engineering and photogrammetry for diagnostics in Orthodontics. Journal of Dental Research, 87(B), 1620.
Deli, R., Di Gioia, E., Galantucci, L.M., & Percoco, G. (2008). Non-invasive photogrammetric technique for 3D automatic measurement of faces. 84th EOS Congress of the European Orthodontics Society, #287P, Lisbon (Pt), 10–14 June.
Kovacs, L., Zimmermann, A., Brockmann, G., Gu ̈hring, M., Baurecht, H., Papadopulos, N.A., Schwenzer-Zimmerer, K., Sader, R., Biemer, E., & Zeilhofer (2006). 3D recording of the human face with a laser scanner. Journal of Plastic, Reconstructive & Aesthetic Surgery, 59, 1193–1202.
Winder, R.J., Darvann, T.A., McKnightc, W., Mageed, J.D.M., & Ramsay-Baggs, P. (2008). Technical validation of the Di3D stereophotogrammetry surface imaging system. British Journal of Oral and Maxillofacial Surgery, 46, 33–37.
Sforza, C. (2006). Three-dimensional, non invasive analysis of craniofacial growth during deciduous and early mixed dentition. Ortognatodonzia Italiana, 13(1), 53–62.
Sforza, C., Peretta, R., Grandi, G., Farronato, G., & Ferrario, V.F. (2007). 3D facial morphometry in skeletal Class III patients: A non-invasive study of soft-tissue changes before and after orthognathic surgery. British Journal of Oral and Maxillofacial Surgery, 45, 138–144.
Farkas, L. (1994). Anthropometry of the head and face. New York: Raven Press.
Kau, C.H., Hunter, L.M., & Hingston, E.J. (2007). A different look: 3D facial imaging of a child with Binder syndrome. American Journal of Orthodontics and Dentofacial Orthopedics, 132(5), 704–709.
Ferrario, V.F., Sforza, C., Schmitz, J.H., Miani, A., & Taroni, G. (Dec 1995). Fourier analysis of human soft tissue facial shape: Sex differences in normal adults. Journal of Anatomy, 187 (Pt 3), 593–602.
Ayoub, A.F., Xiao, Y., Khambay, B., Siebert, J.P., & Hadley, D. (2007). Towards building a photo-realistic virtual human face for craniomaxillofacial diagnosis and treatment planning. International Journal of Oral and Maxillofacial Surgery, 36, 423–428.
Ayoub, A.F., Siebert, P., Moos, K.F., Wray, D., Urquhart, Q.C., & Niblett, T.B. (1998). A vision based 3D capture system for maxillofacial assessment & surgical planning. British Journal of Oral and Maxillofacial Surgery, 36, 353–357.
Acknowledgments
This research has been funded by the Italian Ministry of Research and University by the Relevant National Interest Projects Program PRIN 2007 awarded to the Politecnico di Bari University (Coordinator Prof. L.M. Galantucci) and the Università Cattolica del Sacro Cuore di Roma (Coordinator Prof. R. Deli).
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Galantucci, L.M., Percoco, G., Gioia, E.D. (2009). Low Cost 3D Face Scanning Based on Landmarks and Photogrammetry. In: Huang, X., Ao, SI., Castillo, O. (eds) Intelligent Automation and Computer Engineering. Lecture Notes in Electrical Engineering, vol 52. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3517-2_8
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DOI: https://doi.org/10.1007/978-90-481-3517-2_8
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