Active Self-calibration of Multi-camera Systems

We present a method for actively calibrating a multi-carnera system consisting of pan-tilt zoom cameras. After a coarse initial calibration, we determine the probability of each relative pose using a probability distribution based on the camera images. The relative poses are optimized by rotating and zooming each camera pair in a way that significantly simplifies the problem of extracting correct point correspondences. In a final step we use active camera control, the optimized relative poses, and their probabilities to calibrate the complete multi-camera system with a minimal number of relative poses. During this process we estimate the translation scales in a camera triangle using only two of the three relative poses and no point correspondences. Quantitative experiments on real data outline the robustness and accuracy of our approach.