Machine Vision and Applications

, Volume 27, Issue 3, pp 377–385

Realistic surface geometry reconstruction using a hand-held RGB-D camera

Original Paper

DOI: 10.1007/s00138-016-0747-9

Cite this article as:
Lee, KR. & Nguyen, T. Machine Vision and Applications (2016) 27: 377. doi:10.1007/s00138-016-0747-9

Abstract

In this paper, we have proposed a novel approach for the reconstruction of real object/scene with realistic surface geometry using a hand-held, low-cost, RGB-D camera. To achieve accurate reconstruction, the most important issues to consider are the quality of the geometry information provided and the global alignment method between frames. In our approach, new surface geometry refinement is used to recover finer scale surface geometry from depth data by utilizing high-quality RGB images. In addition, a weighted multi-scale iterative closest point method is exploited to align each scan to the global model accurately. We show the effectiveness of the proposed surface geometry refinement method by comparing it with other depth refinement methods. We also show both the qualitative and quantitative results of reconstructed models by comparing it with other reconstruction methods.

Keywords

3D reconstruction Kinect RGB-D images SLAM Volumetric representation Real time 

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of California San DiegoLa JollaUSA