RGBTSDF: An Efficient and Simple Method for Color Truncated Signed Distance Field (TSDF) Volume Fusion Based on RGB-D Images
发布时间：2025-01-07 点击次数：
DOI码：10.3390/rs16173188
所属单位：School of Remote Sensing and Information Engineering, Wuhan University, China
发表刊物：REMOTE SENSING
关键字：RGB-D,TSDF,3D reconstruction,octree
摘要：RGB-D image mapping is an important tool in applications such as robotics, 3D reconstruction, autonomous navigation, and augmented reality (AR). Efficient and reliable mapping methods can improve the accuracy, real-time performance, and flexibility of sensors in various fields. However, the currently widely used Truncated Signed Distance Field (TSDF) still suffers from the problem of inefficient memory management, making it difficult to directly use it for large-scale 3D reconstruction. In order to address this problem, this paper proposes a highly efficient and accurate TSDF voxel fusion method, RGBTSDF. First, based on the sparse characteristics of the volume, an improved grid octree is used to manage the whole scene, and a hard coding method is proposed for indexing. Second, during the depth map fusion process, the depth map is interpolated to achieve a more accurate voxel fusion effect. Finally, a mesh extraction method with texture constraints is proposed to overcome the effects of noise and holes and improve the smoothness and refinement of the extracted surface. We comprehensively evaluate RGBTSDF and similar methods through experiments on public datasets and the datasets collected by commercial scanning devices. Experimental results show that RGBTSDF requires less memory and can achieve real-time performance experience using only the CPU. It also improves fusion accuracy and achieves finer grid details.
合写作者：Hu, Pengcheng,Zhao, Xujie,Ding,Chen, Shuowen,Huang, Yunqiang,Li,Zhang, Qingwu, Ying, Yong
论文类型：期刊论文
学科门类：工学
文献类型：J
卷号：16
期号：17
是否译文：否
CN号：WOS:001311462000001
发表时间：2024-09-01
