We describe a novel automatic calibration method using a single camera for a multiple-projector spherical Fish Tank Virtual Reality (FTVR) display. Modelling the projector as an inverse camera, we estimate the intrinsic and extrinsic projector parameters automatically using a set of projected images on the spherical screen. A calibrated camera is placed beneath to observe partially visible projected patterns. Using the correspondence between the observed pattern and the projected pattern, we reconstruct the shape of the spherical display and finally recover the 3D position of each projected pixel on the display. Additionally we present a practical calibration evaluation method that estimates on-surface accuracy using the single camera. We use point mismatch as a metric to describe misalignment and line mismatch to describe distortion. We demonstrate our automatic approach can achieve an on-surface point mismatch less than $1mm$ and line mismatch less than one degree on a 30cm diameter spherical screen. Taken together, our calibration approach and evaluation method are automatic and accurate for a desktop spherical FTVR and can be applied to other multiple-projector displays with curved screens.

Presented at the IEEE Winter Conference on Applications of Computer Vision in Santa Rosa, March 2017.