The standardization of evaluation techniques for building extraction is an unresolved issue in the fields of remote sensing, photogrammetry, and computer vision. In this letter, we propose a metric with a working title ?{PoLiS} metric? to compare two polygons. The {PoLiS} metric is a positive-definite and symmetric function that satisfies a triangle inequality. It accounts for shape and accuracy differences between the polygons, is straightforward to apply, and requires no thresholds. We show through an example that the {PoLiS} metric between two polygons changes approximately linearly with respect to small translation, rotation, and scale changes. Furthermore, we compare building polygons extracted from a digital surface model to the reference building polygons by computing {PoLiS}, Hausdorff, and Chamfer distances. The results show that quantification by the {PoLiS} distance of the dissimilarity between polygons is consistent with visual perception. Furthermore, Hausdorff and Chamfer distances overrate the dissimilarity when one polygon has more vertices than the other. We propose an approach toward standardizing building extraction evaluation, which may also have broader applications in the field of shape similarity.     «

The standardization of evaluation techniques for building extraction is an unresolved issue in the fields of remote sensing, photogrammetry, and computer vision. In this letter, we propose a metric with a working title ?{PoLiS} metric? to compare two polygons. The {PoLiS} metric is a positive-definite and symmetric function that satisfies a triangle inequality. It accounts for shape and accuracy differences between the polygons, is straightforward to apply, and requires no thresholds. We show th...     »