Name
Title | ||
|---|---|---|
Silhouette-based three dimensional image registration using CMA-ES with joint scheme of partial restart and variable fixing. |
Abstract | ||
|---|---|---|
This paper proposes a three-dimensional (3D) entire shape reconstruction method that performs simultaneous 3D registration of multiple depth images obtained from multiple viewpoints. With the combination of a silhouette-based objective function and evolutionary computation algorithms, the proposed method realizes the entire shape reconstruction from small number (two or three) of depth images, which do not involve enough overlapping regions for other 3D registration methods. In particular, this paper proposes a CMA-ES algorithm with regional intensification techniques (CMA-ESPR+VF) to speed up the registration process. Experimental results show that the proposed CMA-ESPR+VF achieved a speedup that is at most 18 times faster than self-adaptive differential evolution.
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Year | Venue | Field |
|---|---|---|
2018 | GECCO (Companion) | Small number,Computer vision,Silhouette,Computer science,Evolutionary computation,Differential evolution,CMA-ES,Artificial intelligence,Shape reconstruction,Machine learning,Image registration,Speedup |
DocType | ISBN | Citations |
Conference | 978-1-4503-5764-7 | 0 |
PageRank | References | Authors |
0.34 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takuto Shigenobu | 1 | 0 | 0.34 |
| Takuya Ushinohama | 2 | 0 | 0.34 |
| hiroshi kawasaki | 3 | 274 | 50.85 |
| Satoshi Ono | 4 | 219 | 39.83 |