| With the rapid development of Internet and multimedia technology,the digital videos have become more and more popular in people’s daily life.People can easily use mobile phones and other portable devices to shoot digital videos;numerous online video playback sites have sprung up;large video databases are increasingly common in life.How to effectively store and manage a large amount of video content information becomes an urgent problem to be solved.In addition,with the richness and the various varieties of the video content,people urgently need a fast and effective way to understand the information that videos carry.However,to better understand and analysis the videos,it is inevitable to do much video data processing work,which is not easy in the practical applications.Extracting the key frame sequences of the video sequences can solve the problem above well,that is,the main content information of the original video sequences is represented by a set of representative video frame sequences.In this thesis,we first introduce the relevant knowledge of video key frame extraction.Based on this,a new method to effectively extract video key frames is presented.We first calculate the relative entropy(RE)or the square root of relative entropy(SRRE)between adjacent frames of the video,as the difference between adjacent frames.Then the statistical outlier detection algorithm Studentized Deviate Extreme(ESD)is utilized to identify outliers.Then we find the optimal segmentation threshold to locate the shot boundary through the method of polynomial regression,and implement the adaptive shot segmentation of video sequences.In order to further analyze the content information in each video shot,we subdivide the video shots into different types,according to the extent of variation of the shot content,then extract key frames in each sub shot.In addition,this thesis proposes a multi scale abstract scheme for video key frames based on the hierarchical strategy.Extensive experimental results of a large amount of video data indicate that,compared with other methods,the proposed method has better performance,in terms of both the objective and subjective evaluation.Meanwhile,the new method achieves the basic universality and real-time effect. |
