A topological approach to finding grids in calibration patterns

Authors:
Chang Shu;Alan Brunton;Mark Fiala
Affiliations:
National Research Council Canada, Institute for Information Technology, Montreal Road, Building M-50, K1A 0R6, Ottawa, ON, Canada;National Research Council Canada, Institute for Information Technology, Montreal Road, Building M-50, K1A 0R6, Ottawa, ON, Canada;National Research Council Canada, Institute for Information Technology, Montreal Road, Building M-50, K1A 0R6, Ottawa, ON, Canada
Venue:
Machine Vision and Applications
Year:
2010

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Abstract

This paper describes a technique for finding regular grids in the images of calibration patterns, a crucial step in calibrating cameras. Corner features located by a corner detector are connected using Delaunay triangulation. Pairs of neighboring triangles are combined into quadrilaterals, which are then topologically filtered and ordered. Both triangular and quadrilateral elements are represented by a single mesh data structure, which allows us to exploit the strong topological constraints in a regular grid. The complexity of the algorithm is linear to the number of corners. Experiments show that the method is able to handle images with severe radial distortions and partial pattern occlusions. Implemented on a conventional desktop, grid matching can be done in real time. The method is also applicable to marker detections for augmented reality and robot navigation.