Normalized videosnapping: A non-linear video synchronization approach

Video synchronization is the task of content-based alignment of two or more videos depicting the same event with spatial variations or in the same object with temporal changes. Video synchronization is one of the most fundamental tasks when it comes to manipulations with temporally or spatially multi-perspective video-shots. In this paper, a model is proposed to deal with the synchronization problem and efficiently tackles issues arising during synchronizing two videos. Here, videos are dealt, at the frame level with features from each frame forming the basis of alignment. Features are matched and mapped to generate a cost matrix of similarities among the frames of the videos in concern. A modified version of Djikstra's algorithm that yields an optimal path through the matrix is applied. Through an optimal path, events are grouped into adjacent regions following which temporal warpings are introduced into the videos to achieve the best possible alignment among them. The model has proven to be efficient and compatible with all classes of quality levels of videos.