Video Summarization Using Adaptive Shot Detection and Statistical Aproach to Estimate the Motion
Wafae Sabbar, Adil Chergui, Abdelkrim Bekkhoucha
Journal of Information Organization, Vol. 2, No. 3, 2012.
DOI: 
Link: http://www.dline.info/jio/fulltext/v2n3/1.pdf
Abstract:
The video summarization is the process to present a rapid view of the important video scenes. It is a necessary step to create an efficient system of indexing and retrieve video. Mainly summarization methods apply a clustering algorithm, which use the dissimilarity matrix calculated between all video frames to extract the key frames which imply a quadratic calculation. To reduce this complexity, we propose a hierarchical approach to extract video summary based on shot segmentation and motion estimation. In the first step, we use an adaptive detection of shot transitions to segment the video in shots. In the next step, we apply a hierarchical clustering in each detected shots to extract the keyframes; the number of these keyframes is adaptive to the motion in the shot. We propose a statistical approach using a co-occurrence matrix to estimate this motion. To validate the effectiveness of the proposed approach, we present some experiment results based on real video.