Robust 3-D Object Skeletonisation for the Similarity Measure

Christian Feinen, David Barnowsky, Dietrich Paulus, Marcin Grzegorzek


In this paper we introduce our approach for similarity measure of 3-D objects based on an existing curve skeletonization technique. This skeletonization algorithm for 3-D objects delivers skeletons thicker than 1 voxel. This makes an efficient distance or similarity measure impossible. To overcome this drawback, we use a significantly extended skeletonization algorithm (by Reniers) and a modified Dijkstra approach. In addition to that, we propose features that are directly extracted from the resulting skeletal structures. To evaluate our system, we created a ground truth of 3-D objects and their similarities estimated by humans. The automatic similarity results achieved by our system were evaluated against this ground truth in terms of precision and recall in an object retrieval setup.


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Paper Citation

in Harvard Style

Feinen C., Barnowsky D., Paulus D. and Grzegorzek M. (2013). Robust 3-D Object Skeletonisation for the Similarity Measure . In Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-8565-41-9, pages 167-175. DOI: 10.5220/0004255601670175

in Bibtex Style

author={Christian Feinen and David Barnowsky and Dietrich Paulus and Marcin Grzegorzek},
title={Robust 3-D Object Skeletonisation for the Similarity Measure},
booktitle={Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},

in EndNote Style

JO - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Robust 3-D Object Skeletonisation for the Similarity Measure
SN - 978-989-8565-41-9
AU - Feinen C.
AU - Barnowsky D.
AU - Paulus D.
AU - Grzegorzek M.
PY - 2013
SP - 167
EP - 175
DO - 10.5220/0004255601670175