SVM Based Shot Boundary Detection Using Block Motion Feature Based on Statistical Moments

Temporal video segmentation is of fundamental importance in order to facilitate user’s access to huge volume of video data as well as for video summarization.The objective of shot boundary detection is to partition the video into meaningful, basic structural units called shots. In this paper, a shot boundary detection technique has been proposed for cuts. The method extracts block feature based similarities from the frames of the input video. Statistical moments up to second order are used to measure the motion present in the frames. Feature vectors are generated using a sliding window over time and are trained by a SVM to identify the cuts.