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.
|Title of host publication||VISAPP 2013 : Proceedings of the International Conference on Computer Vision Theory and Applications, Barcelona, Spain, February 21-24, 2013|
|Publication status||Published - 2013|
|Event||8th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2013) - Barcelona, Spain|
Duration: 21 Feb 2013 → 24 Feb 2013
Conference number: 8
|Conference||8th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2013)|
|Abbreviated title||VISIGRAPP 2013|
|Period||21/02/13 → 24/02/13|
Kustra, J., Jalba, A. C., & Telea, A. C. (2013). Probabilistic view-based 3D curve skeleton computation on the GPU. In VISAPP 2013 : Proceedings of the International Conference on Computer Vision Theory and Applications, Barcelona, Spain, February 21-24, 2013 (Vol. 2, pp. 237-246). INSTICC Press.