Dissimilarity Detection of Two Video Sequences

This paper presents an approach for detection of differences between two visually identical video sequences. The video processing task for detection of short- and long-term changes between two video sequences is defined in detail. The algorithm comparing two video sequences (reference and query) is introduced together with definition of particular situations that the algorithm must be able to detect: re-written parts, removals or injected parts. The image processing methods are selected to be robust to several practical distortions that might appear in defined task. The appropriate computer-vision methods are presented and discussed, then proposed method and experiments are introduced and evaluated on manually generated dataset. Main focus of this work is on comparison of two different approaches for keyframe extraction: The first, more robust one is based on local features tracking, which we attempt to replace with computationally much less-expensive global descriptor approach with preservation of approximately the same video sequence dissimilarities detection success rate. Results of the different approaches are presented and discussed.