Name
Abstract | ||
|---|---|---|
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. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Computer Vision and Pattern Recognition | Computer vision,Heuristic,Pattern recognition,Computer science,Mean curvature,Gaussian,Artificial intelligence,Initialization,Reflectivity,Photometric stereo,3D reconstruction,Dijkstra's algorithm |
DocType | Volume | Citations |
Journal | abs/1802.06140 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Khanian | 1 | 0 | 0.34 |
| Ali Sharifi Boroujerdi | 2 | 12 | 2.25 |
| Michael Breuß | 3 | 168 | 25.45 |