Abstract

In this work we present a method to synchronize video se- quences 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 estab- lish sub-frame video synchronization. While contemporary synchroniza- tion 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 synchro- nization. To this end, we propose a novel symmetric transfer error which is dynamically minimized, and reduces the propagation of error from fea- ture 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 quan- titative 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.