电子学报2017，Vol.45Issue(5)：1035-1043,9.DOI:10.3969/j.issn.0372-2112.2017.05.002
基于超图排序算法的视频摘要
Video Summarization with Hyper-Graph Ranking
摘要
Abstract
Video summarization has received widely attention as a technique to quickly display the main video content.Existing graph model based method takes video frames as vertices and uses the edges to build the relationship between two vertices,which may not well capture the complex relationship among the video frames.To overcome this drawback,we present a novel method based on hyper-graph ranking to generate a static video summarization,and name it Hyper-Graph Ranking based Video Summarization (HGRVS).Specifically,HGRVS first builds a video hyper-graph model to connect the video frames that have internal relations with hyper-edges;then classifies the video frames with an idea borrowed from the hyper-graph ranking method to provide the candidate keyframes;the video summarization is finally determined with the keyframes chosen by an objective function.Extensive subjective and objective experiments on the popular Open Video Project and YouTube datasets clearly demonstrate the superiority of HGRVS to the state-of-the-art approaches.关键词
视频摘要/超图/超图排序/视频帧分类/关键帧提取Key words
video summarization/hyper-graph/hyper-graph ranking/video frames classification/keyframe extraction分类
信息技术与安全科学引用本文复制引用
冀中,樊帅飞..基于超图排序算法的视频摘要[J].电子学报,2017,45(5):1035-1043,9.基金项目
国家自然科学基金(No.61472273) （No.61472273）
