Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial Network
Recently, three-dimensional (3D) content used in various fields has attracted attention owing to the development of virtual reality and augmented reality technologies. To produce 3D content, we need to model the objects as vertices. However, high-quality modeling is time-consuming and costly. Drawin...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-08-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/16/7536 |
| _version_ | 1797524724314537984 |
|---|---|
| author | Kyungho Yu Juhyeon Noh Hee-Deok Yang |
| author_facet | Kyungho Yu Juhyeon Noh Hee-Deok Yang |
| author_sort | Kyungho Yu |
| collection | DOAJ |
| description | Recently, three-dimensional (3D) content used in various fields has attracted attention owing to the development of virtual reality and augmented reality technologies. To produce 3D content, we need to model the objects as vertices. However, high-quality modeling is time-consuming and costly. Drawing-based modeling is a technique that shortens the time required for modeling. It refers to creating a 3D model based on a user’s line drawing, which is a 3D feature represented by two-dimensional (2D) lines. The extracted line drawing provides information about a 3D model in the 2D space. It is sometimes necessary to generate a line drawing from a 2D cartoon image to represent the 3D information of a 2D cartoon image. The extraction of consistent line drawings from 2D cartoons is difficult because the styles and techniques differ depending on the designer who produces the 2D cartoons. Therefore, it is necessary to extract line drawings that show the geometric characteristics well in 2D cartoon shapes of various styles. This paper proposes a method for automatically extracting line drawings. The 2D cartoon shading image and line drawings are learned using a conditional generative adversarial network model, which outputs the line drawings of the cartoon artwork. The experimental results show that the proposed method can obtain line drawings representing the 3D geometric characteristics with a 2D line when a 2D cartoon painting is used as the input. |
| first_indexed | 2024-03-10T09:01:23Z |
| format | Article |
| id | doaj.art-6e5e9577e4334ec89cc0a7e6c0c4a9c9 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T09:01:23Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-6e5e9577e4334ec89cc0a7e6c0c4a9c92023-11-22T06:43:08ZengMDPI AGApplied Sciences2076-34172021-08-011116753610.3390/app11167536Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial NetworkKyungho Yu0Juhyeon Noh1Hee-Deok Yang2Department of Computer Engineering, Chosun University, 309 Pilmun-Daero, Dong-Gu, Gwangju 61452, KoreaDepartment of Computer Engineering, Chosun University, 309 Pilmun-Daero, Dong-Gu, Gwangju 61452, KoreaDepartment of Computer Engineering, Chosun University, 309 Pilmun-Daero, Dong-Gu, Gwangju 61452, KoreaRecently, three-dimensional (3D) content used in various fields has attracted attention owing to the development of virtual reality and augmented reality technologies. To produce 3D content, we need to model the objects as vertices. However, high-quality modeling is time-consuming and costly. Drawing-based modeling is a technique that shortens the time required for modeling. It refers to creating a 3D model based on a user’s line drawing, which is a 3D feature represented by two-dimensional (2D) lines. The extracted line drawing provides information about a 3D model in the 2D space. It is sometimes necessary to generate a line drawing from a 2D cartoon image to represent the 3D information of a 2D cartoon image. The extraction of consistent line drawings from 2D cartoons is difficult because the styles and techniques differ depending on the designer who produces the 2D cartoons. Therefore, it is necessary to extract line drawings that show the geometric characteristics well in 2D cartoon shapes of various styles. This paper proposes a method for automatically extracting line drawings. The 2D cartoon shading image and line drawings are learned using a conditional generative adversarial network model, which outputs the line drawings of the cartoon artwork. The experimental results show that the proposed method can obtain line drawings representing the 3D geometric characteristics with a 2D line when a 2D cartoon painting is used as the input.https://www.mdpi.com/2076-3417/11/16/7536line drawingconditional generative adversarial networks |
| spellingShingle | Kyungho Yu Juhyeon Noh Hee-Deok Yang Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial Network Applied Sciences line drawing conditional generative adversarial networks |
| title | Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial Network |
| title_full | Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial Network |
| title_fullStr | Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial Network |
| title_full_unstemmed | Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial Network |
| title_short | Line Drawing Extraction from Cartoons Using a Conditional Generative Adversarial Network |
| title_sort | line drawing extraction from cartoons using a conditional generative adversarial network |
| topic | line drawing conditional generative adversarial networks |
| url | https://www.mdpi.com/2076-3417/11/16/7536 |
| work_keys_str_mv | AT kyunghoyu linedrawingextractionfromcartoonsusingaconditionalgenerativeadversarialnetwork AT juhyeonnoh linedrawingextractionfromcartoonsusingaconditionalgenerativeadversarialnetwork AT heedeokyang linedrawingextractionfromcartoonsusingaconditionalgenerativeadversarialnetwork |