Modelling the non-stationary videos for performance assessment of frame reconstruction

Usually public datasets involving non-stationary video sequences do not have the corresponding ground-truth stationary videos. This means that the performance assessment of reconstructed videos using the wide spread full-reference metrics is impossible. For this purpose, we propose a set of models simulating the shaking camera motion in real-life applications, such as the hand-held shooting and shooting from unmanned aerial vehicles and moving platforms. First, the stationary video sequence is analyzed carefully. 3D camera path is built using the pseudo-disparity values between the consecutive frames based on the corresponding feature points. This high cost procedure permits to build a relatively smooth camera path in 3D space with the non-significant jitters. Second, the end-user chooses the duration, position, and type of shake and/or jitters in video sequence. Third, the desired simulation is implemented in wavelet domain. The distortions, such as displacements, rotations, and local/global blurring, are simulated depending on the chosen situation. We use the physically-based and sample models. In order to reach the ground-truth demonstration, we crop the original frames. If RGB-D video is available, then realistic perspective projections of shaking synthesized video can be created.