Abstract
Photometric sampling is a process where the surface normals of an object are estimated through the excitation of the object’s surface and a rotating light source around it. The method can be regarded as a special case of photometric stereo when extensive sampling is performed in order to calculate surface normals. The classic photometric sampling approach considers only variations around the azimuth angle of the moving light source. As a consequence, additional attention has to be be paid to the recovery of the light source directions and the removal of specular and shadowed regions. This paper investigates the effect of including variations around the zenith angle of the light source vector in a photometric sampling framework, developing a geometric approach to estimate the surface normal vectors. Experiments show that increasing the number of samples along the zenith variation benefits the estimation of the surface normals.
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Hernández-Rodríguez, F., Castelán, M. (2012). Extended Photometric Sampling for Surface Shape Recovery. In: Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F., Olvera López, J.A., Boyer, K.L. (eds) Pattern Recognition. MCPR 2012. Lecture Notes in Computer Science, vol 7329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31149-9_6
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DOI: https://doi.org/10.1007/978-3-642-31149-9_6
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