Video sequence synchronization is often necessary for computer vision applications where multiple simultaneously recorded videos are processed. We present a coarse-to-fine approach to synchronizing two video sequences recorded at the same frame rate by stationary cameras with fixed internal parameters. At the coarse level, each sequence is broken into a set of sub-sequences, which are then matched. A voting scheme determines the range in which the sequences? temporal offset lies. The fine synchronization step searches for the temporal offset by initially examining integer offsets, and then using the golden-section search to locate the offset to sub-frame accuracy. Our algorithm recovers the temporal offset of two sequences using the motion of a single moving object, is computationally efficient, and it does not require any stationary background points as reference points. We present results for synthetic data and real video sequences, with various degrees of temporal overlap.