Optimal key frame selection using visual content metric

Key frame selection is the process to select the most representative frames of a long video sequence based on a given set of rules. This paper presents a novel algorithm for selecting a set of representative frames in MPEG compressed video. We use a luminance DCT DC value, macroblock type and motion vector information to determine the motion activity and visual content change in MPEG compressed video. The advantages of this algorithm are highly accurate video content description and efficient extraction of the required information in the MPEG compressed domain by low complexity inverse quantization and variable length decoding. A visual content based key frame selection is proposed. One of the advantages of this approach is that it does not depend on any predefined threshold or parameter, It gives a set of key frames based on an objective model of visual content flow. Another advantage is that the predefined number of key frames can be obtained by using the proposed algorithm.