An Enhanced Structure-from-Motion Paradigm Based on the Absolute Dual Quadric and Images of Circular Points

Lilian Calvet, Pierre Gurdjos; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2013, pp. 985-992

This work aims at introducing a new unified Structurefrom-Motion (SfM) paradigm in which images of circular point-pairs can be combined with images of natural points. An imaged circular point-pair encodes the 2D Euclidean structure of a world plane and can easily be derived from the image of a planar shape, especially those including circles. A classical SfM method generally runs two steps: first a projective factorization of all matched image points (into projective cameras and points) and second a camera selfcalibration that updates the obtained world from projective to Euclidean. This work shows how to introduce images of circular points in these two SfM steps while its key contribution is to provide the theoretical foundations for combining "classical" linear self-calibration constraints with additional ones derived from such images. We show that the two proposed SfM steps clearly contribute to better results than the classical approach. We validate our contributions on synthetic and real images.