  We present new methods for simultaneously estimating camera geometry and time
shift from video sequences from multiple unsynchronized cameras. Algorithms for
simultaneous computation of a fundamental matrix or a homography with unknown
time shift between images are developed. Our methods use minimal correspondence
sets (eight for fundamental matrix and four and a half for homography) and
therefore are suitable for robust estimation using RANSAC. Furthermore, we
present an iterative algorithm that extends the applicability on sequences
which are significantly unsynchronized, finding the correct time shift up to
several seconds. We evaluated the methods on synthetic and wide range of real
world datasets and the results show a broad applicability to the problem of
camera synchronization.
