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The 3-D reconstruction is relative to constructing a mathematical representation of the scene geometric. In most existing approaches, Lambert's law of the object reflectivity in the scene is explicitly or implicitly assumed. In practice, the law of reflectivity of scene objects differs from Lambert's law as, for example, objects with properties: semi-transparent, transparent, specular, with subsurface scattering effects. This paper proposes an algorithm to estimate a surface reflectance model of 3-D shape and parameters from multiple views. The proposed algorithm includes the following steps: 1) determination of the optical properties of the scanned scene by separating the direct and global lighting components using high-frequency templates; 2) generation of a set of patterns of structured light, the structure of which depends on the optical properties of the scanned scene; 3) scanning the scene using the generated structured light patterns for views non- Lambertian surface; 4) construction of a 3-D model of the scene by triangulating methodology. To solve the problem of determining the views non-Lambertian surface, a 3-D reconstruction algorithm based on a convolutional neural network is proposed. To train the neural network, we apply two stages. At the first stage, the encoder is trained for the descriptor description of the input image. In the second step, a fully connected neural network is added to the encoder for regression for choosing the best views. The coder is trained using the generative adversarial methodology to construct a descriptor description that stores spatial information and information about the optical properties of surfaces located in different areas of the image. The codec network is trained to recover the defect map (depends directly on the sensor and scene properties) from a color image. The architecture of the neural network (generator) is based on the U-Net architecture. As a result, this method uses non-Lambertian properties, and it can compensate for triangulation reconstruction errors caused by viewdependent reflections. Experimental results on both synthetic and real objects are given.
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