CLASSIFICATION OF 3D URBAN SCENES - A Voxel based Approach

Ahmad Kamal Aijazi, Paul Checchin, Laurent Trassoudaine

2012

Abstract

In this paper we present a method to classify urban scenes based on a super-voxel segmentation of sparse 3D data. The 3D point cloud is first segmented into voxels, which are then joined together by using a link-chain method rather than the usual region growing algorithm to create objects. These objects are then classified using geometrical models and local descriptors. In order to evaluate our results a new metric is presented, which combines both segmentation and classification results simultaneously. The effects of voxel size and incorporation of RGB color and intensity on the classification results are also discussed.

Paper Citation

in Harvard Style

Aijazi A., Checchin P. and Trassoudaine L. (2012). CLASSIFICATION OF 3D URBAN SCENES - A Voxel based Approach . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-8425-99-7, pages 61-70. DOI: 10.5220/0003733100610070

in Bibtex Style

@conference{icpram12,
author={Ahmad Kamal Aijazi and Paul Checchin and Laurent Trassoudaine},
title={CLASSIFICATION OF 3D URBAN SCENES - A Voxel based Approach},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2012},
pages={61-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003733100610070},
isbn={978-989-8425-99-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - CLASSIFICATION OF 3D URBAN SCENES - A Voxel based Approach
SN - 978-989-8425-99-7
AU - Aijazi A.
AU - Checchin P.
AU - Trassoudaine L.
PY - 2012
SP - 61
EP - 70
DO - 10.5220/0003733100610070