Name
Abstract | ||
|---|---|---|
This paper discusses a method to reconstruct 3D shape of puppet’s heads from CT images by a machine learning. Our proposed method performs two classes segmentation for wood and other areas in CT images using the U-Net framework. By using this method, we can extract wood parts which consists of 3D shape of puppet’s head. As a result of experiments, some parts cannot be correctly discriminated due to the influence of metal parts. However, we can confirm that most of the wood parts can be extracted correctly. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.23919/SICE56594.2022.9905783 | 2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE) |
Keywords | DocType | ISBN |
Japanese traditional puppet theater,3D shape reconstruction,CT image,machine learning,U-Net | Conference | 978-1-6654-9224-9 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hinata Ikeda | 1 | 0 | 0.34 |
| Hiroyuki Ukida | 2 | 0 | 0.34 |
| Kouki Yamazoe | 3 | 0 | 0.34 |
| Masahide Tominaga | 4 | 0 | 0.34 |
| Tomoyo Sasao | 5 | 0 | 0.34 |
| Kenji Terada | 6 | 0 | 0.34 |