Abstract
In this paper, we present a standard genetic algorithm (SGA) based video abstraction framework, which can adaptively sample video frames in non-uniform way. We formulate the video abstraction as an optimization problem and apply a SGA in the feature space for video abstraction. The video abstraction is accomplished by applying genetic algorithm to search key frames from similar visual content source so that only a small but meaningful amount of information is retained. Experimental results and comparisons are presented to show good performance of our scheme on video static summarization and video skimming.
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