Finding Surface Correspondance for Object Recognition and Registration Using Pairwise Geometric Histograms

Anthony Ashbrook, Robert B. Fisher, Craig Robertson, Naoufel Werghi

Abstract: Pairwise geometric histograms have been demonstrated as an effective descriptor of arbitrary 2-dimensional shape which enable robust and efficient object recognition in complex scenes. In this paper we describe how the approach can be extended to allow the representation and classification of arbitrary 2 1/2- and 3-dimensional surface shape. This novel representation can be used in important vision tasks such as the recognition of objects with complex free-form surfaces and the registration of surfaces for building 3-dimensional models from multiple views. We apply this new representation to both of these tasks and present some promising results.