Implicit surface reconstruction and feature detection with a learning algorithm

Kaye, David; Ivrissimtzis, Ioannis

Abstract

We propose a new algorithm for implicit surface reconstruction and feature detection. The algorithm is based on a self organising map with the connectivity of a regular 3D grid that can be trained into an implicit representation of surface data. The implemented self organising map stores not only its current state but also its recent training history which can be used for feature detection. Preliminary results show that the proposed algorithm gives good quality reconstructions and can detect various types of feature.

Citation

Kaye, D., & Ivrissimtzis, I. (2010, September). Implicit surface reconstruction and feature detection with a learning algorithm. Presented at Theory and Practice of Computer Graphics, Sheffield, UK

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Theory and Practice of Computer Graphics
• Start Date: Sep 6, 2010
• End Date: Sep 8, 2010
• Publication Date: Jan 1, 2010
• Deposit Date: Sep 28, 2010
• Pages: 127-130
• Keywords: Surface reconstruction, Implicit surfaces, Feature detection.
• Public URL: https://durham-repository.worktribe.com/output/1158734
• Publisher URL: http://www.eg.org/EG/DL/LocalChapterEvents/TPCG