Name
Abstract | ||
|---|---|---|
Optical motion capture systems have attracted much interest over the past years, due to their advantages with respect to non-optical counterparts. Moreover, with the technological advances on camera devices, computer graphics and computational methodologies, it becomes technically and economically feasible to consider motion capture systems made of large networks of cameras with embedded communication and processing units on board (i.e., smart cameras). In this case, the approaches relying on the classical 3D reconstruction methods would become inefficient, since their nature is intrinsically centralized. For this reason, we propose a distributed 3D reconstruction algorithm, which relies on a specific organization of cameras to remarkably speed up the scene reconstruction task. Indeed, numerical and experimental results show that the proposed computational scheme overcomes classical centralized solutions, in terms of reconstruction speed. Furthermore, the high processing speed does not compromise the estimation accuracy, since the algorithm is designed to be robust to occlusions and noise.
|
Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3349801.3349818 | Proceedings of the 13th International Conference on Distributed Smart Cameras |
Keywords | Field | DocType |
distributed computation, motion capture systems, smart camera networks | Computer vision,Motion capture,Computer science,Artificial intelligence,3D reconstruction | Conference |
ISBN | Citations | PageRank |
978-1-4503-7189-6 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Angelo Cenedese | 1 | 92 | 27.71 |
| Angelo Cenedese | 2 | 92 | 27.71 |
| Luca Varotto | 3 | 0 | 2.03 |
| Luca Varotto | 4 | 0 | 2.03 |