Detection of Panoramic Takes in Soccer Videos Using Phase Correlation and Boosting

We propose an automatic engine for panoramic-take detection which relies on an algorithm based on phase correlation and boosting. The motion between two sequential video frames is first estimated through a phase correlation. Then, we are able to extract motion parameters and apply post-processing operations on these parameters in order to feed an AdaBoost-based classifier. The proposed algorithm has been validated over 5 segments of videos of 10000 frames each. Panoramic frame detection achieved around 85% recall and 76% accuracy on a validation set of videos not belonging to the training set.