TY - GEN
T1 - Reconstruction using a simple triangle removal approach
AU - Methirumangalath, Subhasree
AU - Parakkat, Amal Dev
AU - Kannan, Shyam Sundar
AU - Muthuganapathy, Ramanathan
N1 - Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/11/27
Y1 - 2017/11/27
N2 - Given a finite set of points P ? R3, sampled from a surface S, surface reconstruction problem computes a model of S from P, typically in the form of a triangle mesh. The problem is ill-posed as various models can be reconstructed from a given point set. In this paper, curve reconstruction in R2, is initially looked at using the Delaunay triangulation (DT) of a point set. The key idea is that the edges in the DT are prioritized and the interior or exterior edges of the DT are removed as long as it has at least one adjacent triangle. Theoretically, it is shown that the reconstruction is homeomorphic to a simple closed curve. Extending this to 3D, an approach based on ‘retaining solitary triangles’ and ‘removing triangles anywhere’ has been proposed. An additional constraint based on the circumradius of a triangle has been employed. Results on public and real-world scanned data, and qualitative/quantitative comparisons with existing methods show that our approach handles diverse features, outliers and noise better or comparable with other methods.
AB - Given a finite set of points P ? R3, sampled from a surface S, surface reconstruction problem computes a model of S from P, typically in the form of a triangle mesh. The problem is ill-posed as various models can be reconstructed from a given point set. In this paper, curve reconstruction in R2, is initially looked at using the Delaunay triangulation (DT) of a point set. The key idea is that the edges in the DT are prioritized and the interior or exterior edges of the DT are removed as long as it has at least one adjacent triangle. Theoretically, it is shown that the reconstruction is homeomorphic to a simple closed curve. Extending this to 3D, an approach based on ‘retaining solitary triangles’ and ‘removing triangles anywhere’ has been proposed. An additional constraint based on the circumradius of a triangle has been employed. Results on public and real-world scanned data, and qualitative/quantitative comparisons with existing methods show that our approach handles diverse features, outliers and noise better or comparable with other methods.
KW - Delaunay triangulation
KW - Point set
KW - Surface reconstruction
U2 - 10.1145/3145749.3149447
DO - 10.1145/3145749.3149447
M3 - Conference contribution
AN - SCOPUS:85040373087
T3 - SIGGRAPH Asia 2017 Technical Briefs, SA 2017
BT - SIGGRAPH Asia 2017 Technical Briefs, SA 2017
PB - Association for Computing Machinery, Inc
T2 - SIGGRAPH Asia 2017 Technical Briefs, SA 2017
Y2 - 27 November 2017 through 30 November 2017
ER -