A Framework for Scalable Summarization of Video

Video summaries provide compact representations of video sequences, with the length of the summary playing an important role, trading off the amount of information conveyed and how fast it can be visualized. This letter proposes scalable summarization as a method to easily adapt the summary to a suitable length, according to the requirements in each case, along with a suitable framework. The analysis algorithm uses a novel iterative ranking procedure in which each summary is the result of the extension of the previous one, balancing information coverage and visual pleasantness. The result of the algorithm is a ranked list, a scalable representation of the sequence useful for summarization. The summary is then efficiently generated from the bitstream of the sequence using bitstream extraction.