Data Augmentation for Semantic Segmentation Using a Real Image Dataset Captured Around the Tsukuba City Hall
-
- Ueda Yuriko
- Department of Computer Science, Graduate School of Science and Technology, Meiji University
-
- Adachi Miho
- Department of Computer Science, Graduate School of Science and Technology, Meiji University
-
- Morioka Junya
- Department of Computer Science, Graduate School of Science and Technology, Meiji University
-
- Wada Marin
- Department of Computer Science, Graduate School of Science and Technology, Meiji University
-
- Miyamoto Ryusuke
- Department of Computer Science, School of Science and Technology, Meiji University
この論文をさがす
抄録
<p>We are exploring the use of semantic scene understanding in autonomous navigation for the Tsukuba Challenge. However, manually creating a comprehensive dataset that covers various outdoor scenes with time and weather variations to ensure high accuracy in semantic segmentation is onerous. Therefore, we propose modifications to the model and backbone of semantic segmentation, along with data augmentation techniques. The data augmentation techniques, including the addition of virtual shadows, histogram matching, and style transformations, aim to improve the representation of variations in shadow presence and color tones. In our evaluation using images from the Tsukuba Challenge course, we achieved the highest accuracy by switching the model to PSPNet and changing the backbone to ResNeXt. Furthermore, the adaptation of shadow and histogram proved effective for critical classes in robot navigation, such as road, sidewalk, and terrain. In particular, the combination of histogram matching and shadow application demonstrated effectiveness for data not included in the base training dataset.</p>
収録刊行物
-
- Journal of Robotics and Mechatronics
-
Journal of Robotics and Mechatronics 35 (6), 1450-1459, 2023-12-20
富士技術出版株式会社
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390861471537539584
-
- NII書誌ID
- AA10809998
-
- ISSN
- 18838049
- 09153942
-
- NDL書誌ID
- 033224231
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- NDL
- Crossref
-
- 抄録ライセンスフラグ
- 使用不可