题名 | DESR: Dynamic Endoscopic Scene Reconstruction Based on Gaussian Splatting |
作者 | |
发表日期 | 2024 |
会议名称 | 9th International Workshop on Pattern Recognition |
会议录名称 | Proceedings of SPIE - The International Society for Optical Engineering
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ISSN | 0277-786X |
卷号 | 13399 |
会议日期 | 2024-06-21——2024-06-23 |
会议地点 | Xiamen |
摘要 | Reconstructing soft tissues in endoscopic videos requires the support of advanced 3D reconstruction technology, which plays a key role in robot-assisted minimally invasive surgery. In this paper, we focus on how to reconstruct dynamic soft tissues as realistically as possible with surgical instruments removed. Due to the limited viewing angle and complex soft tissue deformation, current methods suffer from reconstruction blur and long training time. Inspired by the powerful rendering ability of Gaussian Splatting, we propose a dynamic endoscopic scene reconstruction method which yields better rendering quality and real-time rendering speed. We first utilize depth information to project image to point cloud and give 3D Gaussian points initial positions and colors. The properties of Gaussian points at a certain time stamp are predicted by a MLP deformation module. Our network then renders 3D Gaussian points to get 2D images using a tile-based rasterizer. We design reconstruction losses and color variation loss to optimize the rendering results. Extensive experiments show that our network generates high-fidelity reconstructed endoscopic videos with real-time rendering speed. |
关键词 | Endoscopic scene reconstruction Gaussian Splatting real-time |
DOI | 10.1117/12.3053129 |
URL | 查看来源 |
语种 | 英语English |
Scopus入藏号 | 2-s2.0-85208924471 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/13845 |
专题 | 北师香港浸会大学 |
通讯作者 | Dong,Xiao |
作者单位 | Guangdong Provincial Key Laboratory IRADS,Department of Computer Science,BNU-HKBU United International College,Zhuhai,519087,China |
第一作者单位 | 北师香港浸会大学 |
通讯作者单位 | 北师香港浸会大学 |
推荐引用方式 GB/T 7714 | Fu,Yihang,Dong,Xiao,Miu,Runjieet al. DESR: Dynamic Endoscopic Scene Reconstruction Based on Gaussian Splatting[C], 2024. |
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