Abstract
In this paper a method for reconstructing a specular surface from an image sequence is presented. It is based on tracking both feature points and specularities through the sequence. The feature points are used to calculate the motion of the camera and provide depth information for some points on the boundary of the surface. The specularities give constraints on the surface normal and these constraints are complemented by a smoothness condition in order to estimate the surface shape. The smoothness measure is based on minimizing the surface curvature and a spline representation of the surface is used in the optimization step.
Using the proposed method it is possible to reconstruct completely textureless smooth surfaces. This is shown in both simulated and real experiments.
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Solem, J.E., Heyden, A. (2003). Surface Shape from Specularities. In: Bigun, J., Gustavsson, T. (eds) Image Analysis. SCIA 2003. Lecture Notes in Computer Science, vol 2749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45103-X_110
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DOI: https://doi.org/10.1007/3-540-45103-X_110
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