抄録
Many previous works have proposed methods for reconstructing a three-dimensional (3D) shape from a single image. Some of the methods reconstruct a 3D shape using machine learning. These methods learn the relationship between a 3D shape and a 2D image. However, they cannot learn the desirable features of 2D images for 3D reconstruction, because they use only predefined features. Therefore, this paper presents a method for reconstructing the 3D shape by learning features of a 2D image. This method reconstructs a 3D shape by using Convolutional Neural Network (CNN) for feature learning. The pooling layer and the convolutional layer of the CNN enable us to acquire spatial information of an image and automatically select the valuable feature of the image. From the experimental results using human face images, this method can reconstruct the 3D shape with better accuracy than the previous methods.
本文言語 | English |
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ホスト出版物のタイトル | 2018 International Workshop on Advanced Image Technology, IWAIT 2018 |
出版社 | Institute of Electrical and Electronics Engineers Inc. |
ページ | 1-4 |
ページ数 | 4 |
ISBN(電子版) | 9781538626153 |
DOI | |
出版ステータス | Published - 2018 5月 30 |
イベント | 2018 International Workshop on Advanced Image Technology, IWAIT 2018 - Chiang Mai, Thailand 継続期間: 2018 1月 7 → 2018 1月 9 |
Other
Other | 2018 International Workshop on Advanced Image Technology, IWAIT 2018 |
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国/地域 | Thailand |
City | Chiang Mai |
Period | 18/1/7 → 18/1/9 |
ASJC Scopus subject areas
- コンピュータ ネットワークおよび通信
- コンピュータ ビジョンおよびパターン認識
- メディア記述