Feature-based RGB-D camera pose optimization for real-time 3D reconstruction

• Main Authors: Chao Wang, Xiaohu Guo
• Format: Article
• Language: English
• Published: SpringerOpen 2017-03-01
• Series: Computational Visual Media
• Subjects: camera pose optimization; feature matching; real-time 3D reconstruction; feature correspondence
• Online Access: http://link.springer.com/article/10.1007/s41095-016-0072-2

Abstract In this paper we present a novel feature-based RGB-D camera pose optimization algorithm for real-time 3D reconstruction systems. During camera pose estimation, current methods in online systems suffer from fast-scanned RGB-D data, or generate inaccurate relative transformations between consecutive frames. Our approach improves current methods by utilizing matched features across all frames and is robust for RGB-D data with large shifts in consecutive frames. We directly estimate camera pose for each frame by efficiently solving a quadratic minimization problem to maximize the consistency of 3D points in global space across frames corresponding to matched feature points. We have implemented our method within two state-of-the-art online 3D reconstruction platforms. Experimental results testify that our method is efficient and reliable in estimating camera poses for RGB-D data with large shifts.