High-accuracy camera calibration and scene acquisition

Abstract

In this thesis we present some interesting new approaches in the field of camera calibration and high-accuracy scene acquisition. The first part is devoted to the camera calibration problem exploiting targets composed by circular features. Specifically, we start by improving some previous work on a family of fiducial markers which are leveraged to be used as calibration targets to recover both extrinsic and intrinsic camera parameters. Then, by using the same geometric concepts developed for the markers, we present a method to calibrate a pinhole camera by observing a set of generic coplanar circles.

In the second part we move our attention to unconstrained (non-pinhole) camera models. We begin asking ourselves if such models can be effectively applied also to quasi-central cameras and present a powerful calibration technique that exploit active targets to estimate the huge number of parameters required. Then, we apply a similar method to calibrate a structured-light projector during the range-map acquisition process to improve both the accuracy and coverage. Finally, we propose a way to lower the complexity of a complete unconstrained model toward a pinhole configuration but allowing a complete generic distortion map.

In the last part we study two different scene acquisition problems, namely industry-grade 3D geometry measurements and dichromatic model parameters recovery from multi-spectral images. In the former, we propose a novel visual-inspection device for the dimensional assessment of metallic pipe intakes. In the latter, we formulate a state-of-the-art optimization approach for the simultaneous recovery of the optical flow and the dichromatic coefficients of a scene by analyzing two subsequent frames.