摘要
在视频兴奋时间曲线的基础上提出一种面向用户的体育视频精彩内容自适应检测方法.该方法首先从视觉信息和音频信息中提取底层特征,并建立它们与用户兴奋之间的映射关系.再计算整个视频的兴奋时间曲线.之后,根据曲线的极大值和极小值确定每个精彩片断的位置及其长度,提出"精彩片断重要性"的概念度量每个精彩内容的精彩程度,据此对其进行优先级排序.实验证明本文方法能够从用户角度有效检测大部分体育视频的精彩内容.
An approach to user-orientated sports highlights extraction is proposed based on video excitement time curve. Firstly, some low-level features are extracted from visual and audio information and mapped into users excitement. Then, the excitement time curve of the whole video is computed. Next, the position and the length of each highlight are determined, and all highlights are ranked on the proposed concept of importance-level of highlights. Finally, all highlights are exhibited in a friendly user-interface. Experimental results show the proposed approach can effectively detect most sport video from users' perspective.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2008年第6期782-786,共5页
Pattern Recognition and Artificial Intelligence
基金
国家863计划资助项目(No.2006AA01Z268)
关键词
多媒体信息检索(MIR)
视频摘要
情感计算
精彩内容提取
交互式计算
Multimedia Information Retrieval Highlights Extraction, Interactive ( MIR ), Video Abstraction, Affective Computing, Computing