Optimized KinectFusion Algorithm for 3D Scanning Applications

Faraj Alhwarin, Stefan Schiffer, Alexander Ferrein, Ingrid Scholl

2018

Abstract

KinectFusion is an effective way to reconstruct indoor scenes. It takes a depth image stream and uses the iterative closests point (ICP) method to estimate the camera motion. Then it merges the images in a volume to construct a 3D model. The model accuracy is not satisfactory for certain applications such as scanning a human body to provide information about bone structure health. For one reason, camera noise and noise in the ICP method limit the accuracy. For another, the error in estimating the global camera poses accumulates. In this paper, we present a method to optimize KinectFusion for 3D scanning in the above scenarios. We aim to reduce the noise influence on camera pose tracking. The idea is as follows: in our application scenarios we can always assume that either the camera rotates around the object to be scanned or that the object rotates in front of the camera. In both cases, the relative camera/object pose is located on a 3D-circle. Therefore, camera motion can be described as a rotation around a fixed axis passing through a fixed point. Since the axis and the center of rotation are always fixed, the error averaging principle can be utilized to reduce the noise impact and hence to enhance the 3D model accuracy of scanned object.

Paper Citation

in Harvard Style

Alhwarin F., Schiffer S., Ferrein A. and Scholl I. (2018). Optimized KinectFusion Algorithm for 3D Scanning Applications. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 2: BIOIMAGING; ISBN 978-989-758-278-3, SciTePress, pages 50-57. DOI: 10.5220/0006594700500057

in Bibtex Style

@conference{bioimaging18,
author={Faraj Alhwarin and Stefan Schiffer and Alexander Ferrein and Ingrid Scholl},
title={Optimized KinectFusion Algorithm for 3D Scanning Applications},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 2: BIOIMAGING},
year={2018},
pages={50-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006594700500057},
isbn={978-989-758-278-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 2: BIOIMAGING
TI - Optimized KinectFusion Algorithm for 3D Scanning Applications
SN - 978-989-758-278-3
AU - Alhwarin F.
AU - Schiffer S.
AU - Ferrein A.
AU - Scholl I.
PY - 2018
SP - 50
EP - 57
DO - 10.5220/0006594700500057
PB - SciTePress