Vector R-ordering based selection of segments for video skimming

Vivekraj V. K, Raman Balasubramanian, Debashis Sen

Abstract: Video skimming is a process of generating a shorter yet fully comprehensible version of a given video as its dynamic summary. A generic skimming system involves division of the video into segments and selecting the segments based on their suitability. The suitability is often obtained considering various features of the video and combining their individual contributions. Suggesting that the combination causes loss of information, we propose collective representation of the individual contributions in the form of a vector and use vector reduced (R)-ordering to judge the suitability. R-ordering based tree-structured organization and similarity levels of the video segments are employed to determine the suitability. Comparing with user generated summaries, we show that a video summary generated by a general skimming approach using R-ordering will be more effective in covering the important parts of a given video than when a feature combination is used.