Competing Fronts Watertight Surface Reconstruction

Andrei Sharf, Thomas Lewiner, Ariel Shamir, Leif Kobbelt, Daniel Cohen–Or

The Victoria model is sparse and contains many missing pieces. Our deformable model recovers the shape while

completing missing part is a smooth manner.

Abstract:

We present a deformable model to reconstruct a surface from a point cloud. The model is based on an explicit mesh representation composed of multiple competing evolving fronts. These fronts adapt to the local feature size of the target shape in a coarse–to–fine manner. Hence, they approach towards the finer (local) features of the target shape only after the reconstruction of the coarse (global) features has been completed. This conservative approach leads to a better control and interpretation of the reconstructed topology. The use of an explicit representation for the deformable model guarantees water-tightness and simple tracking of topological events. Furthermore, the coarse–to–fine nature of reconstruction enables adaptive handling of non-homogenous sample density, including robustness to missing data in defected areas.

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Growing a watertight, genus 0 mesh model inside the point cloud of the dragon. In the final step we attach a handle between the body and the tail and project the model onto the point cloud (rightmost figure).

The fronts of our deformable model always move in outward normal direction with a speed defined by the unsigned distance value. Thus, they can move up-hill, from a blue region to a red one, as well as down-hill, passing over local extrema of the guidance field.