Adaptive Key Frames Selection Algorithms for Summarizing Video Data

As multimedia applications are rapidly spread at an ever-increasing rate, the call for efficient and effective methodologies for organizing and manipulating these data becomes a necessity. One of the basic problems that encounters such systems is to find efficient ways to summarize the huge amount of data involved. In this work two sets of algorithms are proposed in order to effectively select key frames from segmented video shots. The algorithms in both sets apply a two-level adaptation mechanism. The first level is done based on the size of the input MPEG file while the second level is performed on a shot-by-shot basis in order to account for the fact that different shots have different levels of activity inside them. Experimental results show the efficiency and robustness of the proposed algorithms in selecting the near optimal set of key frames required to represent each shot in the video stream.