%0 Journal Article
%T Video semantic annotation based on correlative kernel linearneighborhood propagation<br>基于相关核映射线性近邻传播的视频语义标注
%A ZHANG Jian-ming
%A YAN Ting
%A SUN Chun-mei
%A <br>张建明
%A 闫　婷
%A 孙春梅
%J 计算机应用研究
%D 2013
%I 
%X In order to solve the problem that the graph-based semi-supervised learning methods neglect the video consistency in multimedia research area, this paper presented a new method video semantic annotation based on correlative kernel linear neighborhood propagation. The algorithm firstly structured the coefficient by kernel function, and through the coefficient to getting the samples that representative the low feature space. And then according to video correlation modeling, it structured the table between the semantic concepts. Finally, it completed the construction of graph, and used the video information that have been annotated spread to the video that not annotated. After that, the video annotation finished. The experimental results validate the effectiveness and superiority of the proposed method, the process of the video annotation addresses the insufficiency of labeled videos, improves the precision of annotation.
%K semi-supervised learning
%K video consistency
%K video annotation
%K semantic consistency
%K linear neighborhood propagation
%K kernel function<br>半监督学习
%K 视频相关性
%K 视频标注
%K 语义相关性
%K 线性近邻传播
%K 核函数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=51EFA6F8AD100243179E97F8D37F35C1&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=0B39A22176CE99FB&sid=10A39635766FF5D0&eid=5568599C60D4BE87&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=15