Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter - Magboo, Rhell (Animo Repository, 2007)
Quality of the intended motions in a video segment is being affected by external perturbations such as hand shakes, or moving platforms where the camera is mounted. This causes the unwanted jitters in a video that becomes additive to the intended motion. This project aims to remove the unwanted motions in a video segment based on a previously developed algorithm following the general stabilization framework. The inter-frame affine parameters that describe the global motion of a video were measured and the cumulative transformation derived from this. Consequently, the intentional motion was estimated using Kalman filter. The difference between the cumulative transformation and the intended motion was taken as the unwanted motion and shall be used in image compensation. The undefined regions that resulted thereafter image compensation were filled using mosaicking. The project was implemented using MATLAB and is presented in a Graphical User Interface (GUI). The performance of the system was evaluated by computing for the Peak Signal-to-Noise Ratio (PSNR) of the output video. Results showed improvements when compared with the original video sequence. The system was also compared to other video stabilization software available in market.