3D reconstruction, image processing, camera pose estimation, surface fusion
High-quality 3D reconstruction is an important topic in computer graphics and computer vision with many applications, such as robotics and augmented reality. The advent of consumer RGB-D cameras has made a profound advance in indoor scenereconstruction. For the past few years, researchers have spent significant effort to develop algorithms to capture 3D models with RGB-D cameras. As depth images produced by consumer RGB-D cameras are noisy and incomplete when surfaces are shiny, bright, transparent, or far from the camera, obtaining high- quality 3D scene models is still a challenge for existing systems. We here review high-quality 3D indoor scene reconstruction methods using consumer RGB-D cameras. In this paper, we make comparisons and analyses from the following aspects: (i) depth processing methods in 3D reconstruction are reviewed in terms of enhancement and completion, (ii) ICP-based, feature-based, and hybrid methods of camera pose estimation methods are reviewed, and (iii) surface reconstruction methods are reviewed in terms of surface fusion, optimization, and completion. The performance of state-of-the-art methods is also compared and analyzed. This survey will be useful for researchers who want to follow best practices in designing new high-quality 3D reconstruction methods.
Li, Jianwei; Gao, Wei; Wu, Yihong; Liu, Yangdong; and Shen, Yanfei
"High-quality indoor scene 3D reconstruction with RGB-D cameras: A brief review,"
Computational Visual Media: Vol. 8:
3, Article 3.
Available at: https://dc.tsinghuajournals.com/computational-visual-media/vol8/iss3/3