%0 Journal Article
%T Adaptive Video Segmentation Algorithm Using Hidden Conditional Random Fields<br>基于隐条件随机场的自适应视频分割算法
%A CHU Yi-Ping
%A ZHANG Yin
%A YE Xiu-Zi
%A ZHANG San-Yuan
%A <br>褚一平
%A 张引
%A 叶修梓
%A 张三元
%J 自动化学报
%D 2007
%I 
%X Video object segmentation is important for video surveillance and video object tracking,video object recog- nition and video editing.An adaptive video segmentation algorithm based on hidden conditional random fields(HCRFs) is proposed,which models spatio-temporal constraints of video sequence.In order to improve the segmentation quality, the weights of spatio-temporal constraints are adaptively updated by on-line learning of HCRFs.The experimental results have demonstrated that the error ratio of our algorithm is reduced by 23% and 19%,respectively,compared with Gaussian mixture model(GMM)and spatio-temporal Markov random fields(MRF).
%K Video segmentation
%K hidden conditional random fields
%K on-line learning<br>视频分割
%K 隐条件随机场
%K 在线学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=72AEBEE60127D61843230733B4CD0958&yid=A732AF04DDA03BB3&vid=27746BCEEE58E9DC&iid=59906B3B2830C2C5&sid=87352E668344FB84&eid=A35E3FD659BF2630&journal_id=0254-4156&journal_name=自动化学报&referenced_num=2&reference_num=21