Exploiting Homologies in Global Calibration of a Multi-imager Array

Advances in building high-performance camera arrays have opened the opportunity - and challenge - of using these devices for synchronized 3D and multi-viewpoint capture. A requirement of using camera arrays for metric work is that their relative poses be known. With a structured array - that is, one whose imagers' intrinsics and relative positions do not change - it is feasible to perform this calibration once, before any use. We present progress in developing a new approach to this calibration that capitalizes on high quality homographies between pairs of imagers to develop a global optimal solution delivering epipoles and fundamental matrices simultaneously for the entire system. The method exploits what we identify as the rank-one-perturbation-of-identity (ROPI) structure of homologies in posing a unified SVD estimator for the parameters. We summarize the theory, and present both qualitative depictions and quantitative assessments of our results.