Tri-focal tensor-based multiple video synchronization with subframe optimization

In this paper, we present a novel method for synchronizing multiple (more than two) uncalibrated video sequences recording the same event by free-moving full-perspective cameras. Unlike previous synchronization methods, our method takes advantage of tri-view geometry constraints instead of the commonly used two-view one for their better performance in measuring geometric alignment when video frames are synchronized. In particular, the tri-ocular geometric constraint of point/line features, which is evaluated by tri-focal transfer, is enforced when building the timeline maps for sequences to be synchronized. A hierarchical approach is used to reduce the computational complexity. To achieve subframe synchronization accuracy, the Levenberg-Marquardt method-based optimization is performed. The experimental results on several synthetic and real video datasets demonstrate the effectiveness and robustness of our method over previous methods in synchronizing full-perspective videos.