Video Summarization by an Innovative Method in Shot Detection

Abstract

The aim of a video summarization system is to provide a set of key frames which contain the most important parts of video. This system results in efficient storage, quick browsing, and retrieval of collection of video. In this paper, we propose a new summarization system which firstly divides the video into meaningful shots using an innovative and fast method, and then we sample the video frames belonging to each shot which results in 97% reduction in under-process frames. Then, using various characteristics of sampled frames such as color histogram, correlation and moment of inertia, wepropose anadaptive aggregation function for combination of these characteristics (differences) and extraction of key frames. The proposed systemis evaluated using 250 manual key frames constructed by human operators from 50 downloaded videos. The obtained results show that the proposed system provides better results compared to 6 different traditional methods.