摘要
In this paper, we present a sequential video deblurring method based on a spatio-temporal recurrent network for visual SLAM. The method can be applied to any SLAM systems to make sure continuous localization even with blurred images. The quality of the deblurring method is evaluated on real-world problems: Feature points extraction and SLAM, which prove the method can significantly improve the performance of tracking accuracy especially in some severe cases containing strong camera shake or fast motion.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings |
| 出版商 | Institute of Electrical and Electronics Engineers Inc. |
| 页 | 996-997 |
| 页数 | 2 |
| ISBN（电子版） | 9781728113777 |
| DOI | |
| 出版状态 | 已出版 - 3月 2019 |
| 活动 | 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Osaka, 日本 期限: 23 3月 2019 → 27 3月 2019 |
出版系列
| 姓名 | 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings |
|---|
会议
| 会议 | 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 |
|---|---|
| 国家/地区 | 日本 |
| 市 | Osaka |
| 时期 | 23/03/19 → 27/03/19 |
指纹
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Jin, G., Chen, J., Wang, J., & Wang, Y. (2019). A neural motion deblurring approach to restore rich textures for visual SLAM. 在 26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings (页码 996-997). 文章 8797745 (26th IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VR.2019.8797745