Motion activity-based extraction of key-frames from video shots

We describe a key-frame extraction technique based on the intuition that the higher the motion the more the number of key-frames required for summarization. We verify experimentally that the intensity of motion activity directly indicates the summarizability of the video segment, by using the MPEG-7 motion activity descriptor (see Jeannin, S. and Divakaran, A., IEEE Trans. Circuits and Systems for Video Tech., vol.11, no.6, p.720-4, 2001) and the fidelity measure described by H.S. Chang et al. (see IEEE Trans. Circuits and Systems for Video Tech., vol.9, no.8, p.1269-79, 1999). We obtain the key-frames by dividing the shot in parts of equal cumulative motion activity, and then selecting the frame located at the half-way point of each sub-segment. Furthermore, we establish an empirical relationship between the motion activity of a segment and the required number of key-frames. We thus provide a unique and rapid way to find the required number of key-frames and compute them. Our scheme is much faster than conventional color-based key-frame extraction schemes since it relies on simple computation and compressed domain extraction. It is close to the theoretical optimum in accuracy.