  Motivated by the growing demand for interactive environments, we propose an
accurate real-time 3D shape reconstruction technique. To provide a reliable 3D
reconstruction which is still a challenging task when dealing with real-world
applications, we integrate several components including (i) Photometric Stereo
(PS), (ii) perspective Cook-Torrance reflectance model that enables PS to deal
with a broad range of possible real-world object reflections, (iii) realistic
lightening situation, (iv) a Recurrent Optimization Network (RON) and finally
(v) heuristic Dijkstra Gaussian Mean Curvature (DGMC) initialization approach.
We demonstrate the potential benefits of our hybrid model by providing 3D shape
with highly-detailed information from micro-prints for the first time. All
real-world images are taken by a mobile phone camera under a simple setup as a
consumer-level equipment. In addition, complementary synthetic experiments
confirm the beneficial properties of our novel method and its superiority over
the state-of-the-art approaches.
