Detecting polygons of variable dimension in overhead images with particle filters

Abstract

We extend the particle filtering approach to detecting polygonal structures of fixed shape and variable size in overhead images to the more practically useful case of unconstrained side lengths. Our approach deals with multiple candidate sides by validating and clustering particles based on evidence that corners of proper acuteness and orientation (as constrained by the polygon model) might exist. A queue-regulated tracking algorithm that handles multiple candidates across multiple sides is discussed. Compelling detection results in overhead images that involve entire families of polygonal structure are provided.