Mid-scale shot classification for detecting narrative transitions in movie clips
This paper examines classification of shots in video streams for indexing and semantic analysis. We describe an approach to obtain shot motion by making use of motion estimation algorithms to estimate camera movement. We improve prior work by using the four edge regions of a frame to classify No Motion shots. We analyze a neighborhood of shots and provide a new concept, middle-scale classification. This approach relies on automated labeling of frame transitions in terms of motion across adjacent frames. These annotations form a sequential scene-group that correlates with narrative events in the videos. We introduce six middle-scale classes and the corresponding likely sequence content from three clips of the movie The Lord of the Rings : The Return of the King, demonstrate that the middle-scale classification approach successfully extracts a summary of the salient aspects of the movie. We also show direct comparison with prior work on the full movie Matrix.
