"3D indoor scene modeling from RGB-D data: a survey" by Kang Chen, Yu-Kun Lai et al.

Article Title

3D indoor scene modeling from RGB-D data: a survey

Authors

Kang Chen, Tsinghua University, Beijing 100084, China.
Yu-Kun Lai, Cardiff University, Cardiff, CF24 3AA, Wales, UK.
Shi-Min Hu, Tsinghua University, Beijing 100084, China.

Keywords

Keywords RGB-D camera, 3D indoor scenes, geometric modeling, semantic modeling, survey

Abstract

3D scene modeling has long been a fundamental problem in computer graphics and computer vision. With the popularity of consumer-level RGB-D cameras, there is a growing interest in digitizing real-world indoor 3D scenes. However, modeling indoor 3D scenes remains a challenging problem because of the complex structure of interior objects and poor quality of RGB-D data acquired by consumer-level sensors. Various methods have been proposed to tackle these challenges. In this survey, we provide an overview of recent advances in indoor scene modeling techniques, as well as public datasets and code libraries which can facilitate experiments and evaluation.