Abrupt Cut Detection and Key Frame Extration Based on Motion Information

This paper proposes a method of abrupt cut detection based on motion information.Quantitative angle histogram entropy and average magnitude are defined to be the metrics of frame differences from the motion vector filed calculated by block based motion estimation.Adaptive threshold strategies are designed to identify candidate abrupt cuts.False cuts caused by flashes and gradual transitions are eliminated by using a temporal window.In the process of key frame extraction,different algorithms which have different limitations of the number of extraction are selected adaptively according to the extents of similarity of video frames content.Experimental results show that the method has high accuracy and robustness.