Ohrhallinger, S.Mudur, S.Holly Rushmeier and Oliver Deussen2015-02-282015-02-2820131467-8659https://doi.org/10.1111/cgf.12162We present anefficient algorithm for determining an aesthetically pleasing shape boundary connecting all the points in a given unorganized set of 2D points, with no other information than point coordinates. By posing shape construction as a minimisation problem which follows the Gestalt laws, our desired shape Bmin is non‐intersecting, interpolates all points and minimizes a criterion related to these laws. The basis for our algorithm is an initial graph, an extension of the Euclidean minimum spanning tree but with no leaf nodes, called as the minimum boundary complex BCmin. BCmin and Bmin can be expressed similarly by parametrizing a topological constraint. A close approximation of BCmin, termed BC0 can be computed fast using a greedy algorithm. BC0 is then transformed into a closed interpolating boundary Bout in two steps to satisfy Bmin’s topological and minimization requirements. Computing Bmin exactly is an NP (Non‐Polynomial)‐hard problem, whereas Bout is computed in linearithmic time. We present many examples showing considerable improvement over previous techniques, especially for shapes with sharp corners. Source code is available online.We present an efficient algorithm for determining an aesthetically pleasing shape boundary connecting all the points in a given unorganised set of 2D points, with no other information than point coordinates. By posing shape construction as a minimisation problem which follows the Gestalt laws, our desired shape Bmin is non‐intersecting, interpolates all points and minimises a criterion related to these laws. The basis for our algorithm is an initial graph, an extension of the Euclidean minimum spanning tree but with no leaf nodes, called as the minimum boundary complex BCmin. BCmin and Bmin can be expressed similarly by parametrising a topological constraint. A close approximation of BCmin, termed BC0 can be computed fast using a greedy algorithm.curve reconstructiongestalt principlessparse samplingI.3.3 [Computer Graphics]Picture/Image Generation Line and curve generationI.3.5 [Computer Graphics]Computational Geometry and Object Modeling Boundary representationsI.4.8 [Computer Graphics]Scene Analysis Surface Fitting