Depth-Scale Method in 3D Registration of RGB-D Sensor Outputs

Ismail Bozkurt, Egemen Özden

Abstract

Automatic registration of 3D scans with RGB data is studied in this paper. In contrast to bulk of research in the field which deploy 3D geometry consistency, local RGB image feature matches are used to solve the unknown 3D rigid transformation. The key novelty in this work is the introduction of a new simple measure, we call “Depthscale measure”, which logically represents the size of the local image features in 3D world, thanks to the availability of the depth data from the sensor. Depending on the operating characteristics of the target application, we show this measure can be useful and efficient in eliminating outliers through experimental results. Also system level details are given to help scientists who want to build a similar system.

References

  1. Besl, P. J., McKay, N. D., 1992. A Method for Registration of 3-D Shapes. In IEEE PAMI 14, 2, pp.239-256.
  2. Shahram et al., 2011. KinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera. In SIGGRAPH.
  3. Fitzgibbon, A. W., 2001. Robust Registration of 2D and 3D Point Sets. In BMVC.
  4. Bronstein et al., 2010. SHREC 2010: Robust Feature Detection and Description Benchmark. In Eurographics Workshop on 3D Object Retrieval.
  5. Craciun, D., Paparoditis, N., Schmitt, F., 2010. Multi-view Scans Alignment for 3D spherical Mosaicing in Large-
Download


Paper Citation


in Harvard Style

Bozkurt I. and Özden E. (2014). Depth-Scale Method in 3D Registration of RGB-D Sensor Outputs . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 470-475. DOI: 10.5220/0004673204700475


in Bibtex Style

@conference{visapp14,
author={Ismail Bozkurt and Egemen Özden},
title={Depth-Scale Method in 3D Registration of RGB-D Sensor Outputs},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={470-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004673204700475},
isbn={978-989-758-003-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - Depth-Scale Method in 3D Registration of RGB-D Sensor Outputs
SN - 978-989-758-003-1
AU - Bozkurt I.
AU - Özden E.
PY - 2014
SP - 470
EP - 475
DO - 10.5220/0004673204700475