Specular-free residual minimization for photometric stereo with unknown light sources
作者： Tsuyoshi Migita , Kazuhiro Sogawa , Takeshi Shakunaga
DOI: 10.1007/978-3-642-25367-6_16
关键词:
摘要: We address a photometric stereo problem that has unknown lighting conditions. To estimate the shape, reflection properties, and conditions, we employ nonlinear minimization searches for parameters can synthesize images best fit input images. A similar approach been reported previously, but it suffers from slow convergence due to specular parameters. In this paper, introduce specular-free residual avoids negative effects of components by projecting onto complementary space light color. The process simultaneously optimal color other demonstrate effectiveness proposed method using several real synthetic image sets.
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