Photometric approach to surface reconstruction
of artist paintings
Takayuki Hasegawa, Norimichi Tsumura, Toshiya Nakaguchi, Koichi Iino
Journal of Electronic Imaging 20(1), 013006 1-11 (Jan.Mar 2011)
Abstract
We propose a method for surface reconstruction of artist paintings. In
order to reproduce the appearance of a painting, including color, surface
texture, and glossiness, it is essential to acquire the pixel-wise light
reflection property and orientation of the surface and render an image
under an arbitrary lighting condition. A photometric approach is used to
estimate bidirectional reflectance distribution functions (BRDFs) and surface
normals from a set of images photographed by a fixed camera with sparsely
distributed point light sources. A robust and computationally less expensive
nonlinear optimization algorithm is proposed that optimizes the small number
of parameters to simultaneously determine all of the specular BRDF, diffuse
albedo, and surface normal. The proposed method can be applied to moderately
glossy surfaces without separating captured images into diffuse and specular
reflections beforehand. Experiments were conducted using oil paintings
with different surface glossiness. The effectiveness of the proposed method
is validated by comparing captured and rendered images.
Full paper ( to appeare)
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http://dx.doi.org/10.1117/1.3533329