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.

Details

Title
3D indoor scene modeling from RGB-D data: a survey
Author
Chen, Kang 1 ; Yu-Kun, Lai 2 ; Shi-Min, Hu 1 

 Tsinghua University, Beijing, China (GRID:grid.12527.33) (ISNI:0000000106623178) 
 Cardiff University, Cardiff, UK (GRID:grid.5600.3) (ISNI:0000000108075670) 
Pages
267-278
Publication year
2015
Publication date
Dec 2015
Publisher
Springer Nature B.V.
ISSN
20960433
e-ISSN
20960662
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2407020212
Copyright
© The Author(s) 2015. This work is published under https://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.