Abstract
In many realistic scenarios, the use of highly detailed photometric 3D reconstruction techniques is hindered by several challenges in given imagery. Especially, the light sources are often unknown and need to be estimated, and the light reflectance is often non-Lambertian. In addition, when approaching the problem to apply photometric techniques at real-world imagery, several parameters appear that need to be fixed in order to obtain high-quality reconstructions. In this chapter, we attempt to tackle these issues by combining photometric stereo with non-Lambertian preprocessing and Hayakawa lighting estimation. At hand of a dedicated study, we discuss the applicability of these techniques for their use in automated 3D geometry recovery for 3D printing.
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Acknowledgements
The work of Georg Radow was supported by the Deutsche Forschungsgemeinschaft, grant number BR 2245/4-1.
The work of Giuseppe Rodriguez was partially supported by the Regione Autonoma della Sardegna research project “Algorithms and Models for Imaging Science [AMIS]” (RASSR57257, intervento finanziato con risorse FSC 2014-2020—Patto per lo Sviluppo della Regione Sardegna), and the INdAM-GNCS research project “Tecniche numeriche per l’analisi delle reti complesse e lo studio dei problemi inversi.”
The work of Ashkan Mansouri Yarahmadi and Michael Breuß was partially supported by the European Regional Development Fund, EFRE 85037495.
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Radow, G., Rodriguez, G., Yarahmadi, A.M., Breuß, M. (2023). Photometric Stereo with Non-Lambertian Preprocessing and Hayakawa Lighting Estimation for Highly Detailed Shape Reconstruction. In: Cristiani, E., Falcone †, M., Tozza, S. (eds) Mathematical Methods for Objects Reconstruction. INdAM 2021. Springer INdAM Series, vol 54. Springer, Singapore. https://doi.org/10.1007/978-981-99-0776-2_2
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