Outlier-attenuating summarization for user-generated-video

In this paper, the key-frame extraction problem for user-generated-videos which are captured by smart phones is investigated. A collaborative sparse coding model which incorporates the 1/2, 1 and Li, 2 regularization terms are proposed to select few key-frames while attenuating the influences of the outlier frames. Further, the sensors embedded in the smart phone is used to collect the acceleration values, which can be used to improve the performance of outlier-attenuations. Finally, a real dataset is constructed to test the proposed method and the experimental validation shows promising results.