Abstract
We recently introduced a technique that allows 3D information to be captured from a conventional flatbed scanner [22]. The technique requires no hardware modification and allows untrained users to easily capture 3D datasets. Once captured, these datasets can be used for interactive relighting and enhancement of surface detail on physical objects. We have also found that the method can be used to scan and repair damaged photographs. Since only the 3D structure on these photographs will typically be surface tears and creases, our method provides an accurate procedure for automatically detecting these flaws without any user intervention. Once detected, automatic techniques, such as infilling and texture synthesis, can be leveraged to seamlessly repair such damaged areas. We here provide a more thorough exposition and significant new material. We first present a method that is able to repair damaged photographs with minimal user interaction and then show how we can achieve similar results using a fully automatic process.
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Pintus, R., Malzbender, T., Wang, O., Bergman, R., Nachlieli, H., Ruckenstein, G. (2010). Photo Repair and 3D Structure from Flatbed Scanners Using 4- and 2-Source Photometric Stereo. In: Ranchordas, A., Pereira, J.M., Araújo, H.J., Tavares, J.M.R.S. (eds) Computer Vision, Imaging and Computer Graphics. Theory and Applications. VISIGRAPP 2009. Communications in Computer and Information Science, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11840-1_24
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DOI: https://doi.org/10.1007/978-3-642-11840-1_24
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