Optimization of Symmetric Transfer Error for Sub-frame Video Synchronization

In this work we present a method to synchronize video sequences of events that are acquired via uncalibrated cameras at unknown and dynamically varying temporal offsets. Unlike existing methods that synchronize videos of similar events (i.e., videos related to each other through the motion in the scene) up to an integer alignment, we establish sub-frame video synchronization. While contemporary synchronization algorithms implement a unidirectional alignment which biases the results towards a single reference sequence, we adopt a bi-directional or symmetrical alignment approach that results in a more optimal synchronization. To this end, we propose a novel symmetric transfer error which is dynamically minimized, and reduces the propagation of error from feature extraction and spatial mapping into temporal synchronization. The advantages of our approach are validated by tests conducted on (publicly available) real and synthetic sequences. We present qualitative and quantitative comparisons with another state-of-the-art algorithm. A unique application of this work in generating high-resolution 4D MRI data from multiple low-resolution MRI scans is described.