3D-NCuts: Adapting Normalized Cuts to 3D Triangulated Surface Segmentation

Zahra Toony, Denis Laurendeau, Philippe Giguère, Christian Gagné


Being able to automatically segment 3D models into meaningful parts is an important goal in 3D shape processing. In this paper, we are proposing a fast and easy-to-implement 3D segmentation approach, which is based on spectral clustering. For this purpose, we define an improved formulation of the similarity matrix which allows our algorithm to segment both free-form and CAD (Computer Aided Design) 3D models. In 3D space, different shapes, such as planes and cylinders, have different surface normal distributions. We defined the similarity of vertices based on their normals which can segment a 3D model into its geometric features. Results show the effectiveness and robustness of our method in segmenting a wide range of 3D models. Even in the case of complex models, our method results in meaningful segmentations. We tested our segmentation approach on real data segmentation, in the presence of noise and also in comparison with other methods which provided good results in all cases.


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Paper Citation

in Harvard Style

Toony Z., Laurendeau D., Giguère P. and Gagné C. (2014). 3D-NCuts: Adapting Normalized Cuts to 3D Triangulated Surface Segmentation . In Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2014) ISBN 978-989-758-002-4, pages 144-152. DOI: 10.5220/0004692101440152

in Bibtex Style

author={Zahra Toony and Denis Laurendeau and Philippe Giguère and Christian Gagné},
title={3D-NCuts: Adapting Normalized Cuts to 3D Triangulated Surface Segmentation},
booktitle={Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2014)},

in EndNote Style

JO - Proceedings of the 9th International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2014)
TI - 3D-NCuts: Adapting Normalized Cuts to 3D Triangulated Surface Segmentation
SN - 978-989-758-002-4
AU - Toony Z.
AU - Laurendeau D.
AU - Giguère P.
AU - Gagné C.
PY - 2014
SP - 144
EP - 152
DO - 10.5220/0004692101440152