language: en

Task Driven Perceptual Organization for Extraction of Rooftop Polygons

Christopher Jaynes Frank Stolle Robert Collins
Computer Science Department University of Massachusetts
Amherst, MA 01003
Email: @cs.umass.edu

Abstract A new method for extracting planar polygonal rooftops in monocular aerial imagery is proposed. Through bottom-up and top-down construction of perceptual groups, polygons in a single aerial image can be robustly extracted. Orthogonal corners and lines are extracted and hierarchically related using perceptual grouping techniques. Top-down feature verification is used so that features, and links between the features, are verified with local information in the image and weighed in a graph structure according to the underlying support for each feature. Cycles in the graph correspond to possible building rooftop hypotheses. Virtual features are hypothesized for the perceptual completion of partial rooftops. Extraction of the "best" grouping of features into a building rooftop hypothesis is posed as a graph search problem. The maximally weighted, independent set of cycles in the graph is extracted as the final set of roof boundaries.

1. Introduction