Probabilistic View-based 3D Curve Skeleton Computation on the GPU

Jacek Kustra, Andrei Jalba, Alexandru Telea


Computing curve skeletons of 3D shapes is a challenging task. Recently, a high-potential technique for this task was proposed, based on integrating medial information obtained from several 2D projections of a 3D shape (Livesu et al., 2012). However effective, this technique is strongly influenced in terms of complexity by the quality of a so-called skeleton probability volume, which encodes potential 3D curve-skeleton locations. In this paper, we extend the above method to deliver a highly accurate and discriminative curve-skeleton probability volume. For this, we analyze the error sources of the original technique, and propose improvements in terms of accuracy, culling false positives, and speed. We show that our technique can deliver point-cloud curve-skeletons which are close to the desired locations, even in the absence of complex postprocessing. We demonstrate our technique on several 3D models.


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Paper Citation

in Harvard Style

Kustra J., Jalba A. and Telea A. (2013). Probabilistic View-based 3D Curve Skeleton Computation on the GPU . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 237-246. DOI: 10.5220/0004276502370246

in Bibtex Style

author={Jacek Kustra and Andrei Jalba and Alexandru Telea},
title={Probabilistic View-based 3D Curve Skeleton Computation on the GPU},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},

in EndNote Style

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Probabilistic View-based 3D Curve Skeleton Computation on the GPU
SN - 978-989-8565-48-8
AU - Kustra J.
AU - Jalba A.
AU - Telea A.
PY - 2013
SP - 237
EP - 246
DO - 10.5220/0004276502370246