摘要
针对视频检索过程中存在的视频亮度整体漂移、突变干扰以及视频再编辑等问题,提出了一种融合视频指纹特征和关键帧密度的检索算法.该算法首先对视频帧进行区域分割提取视频指纹特征;其次,采用改进的直接时序算法消除亮度漂移等干扰;最后,引入关键帧密度的概念消除了视频再编辑引起的时间跨度问题,同时采用了一种综合的搜索策略.实验结果表明:改进的算法不仅可有效地应对上述问题,而且算法运算量小、查全率与查准率高,具有很好的鲁棒性.
A video retrieval method based on video fingerprints and spatio-temporal information was proposed to solve the problem caused by the whole drift of brightness, interference of abnormal point and video edit. First, the video fingerprint feature was extracted by frame segmentation. Then, an improved direct timing algorithm was used to eliminate the brightness drift interference. Finally, the concept of keyframes density was introduced to eliminate the time span problem caused by video editing and a comprehensive search strategy was presented. Experiment results show that the algorithm can effectively solve these problems with good robustness, low computing burden, and high recall rate and precision.
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2014年第2期200-205,共6页
Journal of Beijing University of Technology
基金
国家自然科学基金资助项目(30970780)
国家博士点基金资助项目(20091103110005)
关键词
视频检索
视频指纹
关键帧密度
基于内容的信息检索
video retrieval
video fingerprints
keyframes density
content-based information retrieval
