Salient frame extraction using support vector regression and motion features

We present a new support vector regression (SVR) algorithm to extract salient frames from videos. We use optical flow to describe motion in frames and an adaptive SVR to identify the abrupt change of content in frame sequences. We show that the proposed algorithm is computationally simple and effective in detecting salient frames in video sequences.