A fast evaluation criterion for the recognition of occluded shapes

Authors:
Secil Ozen;Alexandros Bouganis;Murray Shanahan
Affiliations:
Department of Computing, Imperial College London, 180 Queen's Gate, London SW7 2AZ, UK;Department of Computing, Imperial College London, 180 Queen's Gate, London SW7 2AZ, UK;Department of Computing, Imperial College London, 180 Queen's Gate, London SW7 2AZ, UK
Venue:
Robotics and Autonomous Systems
Year:
2007

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Abstract

A robust and fast object recognition method is crucial in many robotic applications, especially (but not restricted to) in manufacturing. This paper introduces a novel algorithm that satisfies both of these criteria and is capable of recognising a set of model shapes in a complicated scene given as input. The shapes are described using the turning angle representation. Shape matching is carried out by finding the correspondence between the model shape and the input (i.e. corresponding points), and calculating the geometrical transformation of the model that minimises the least square distance between the corresponding points. A new geometric feature is proposed, called ''Generalised Angle'', which facilitates fast elimination of infeasible matches. The Generalised Angle (GA) is invariant to rotation, translation and scaling and does not result in a considerable computational cost to the system. Moreover, an evaluation function is used, which takes several criteria into account and renders the method capable of recognising shapes under occlusion effectively.