%0 Journal Article
%T Quasi-Monte Carlo Filtering for Speaker Tracking<br>基于拟蒙特卡洛滤波的说话人跟踪方法
%A HOU Dai-Wen
%A YIN Fu-Liang CHEN Zhe School of Electronic
%A Information Engineering
%A Dalian Uni- versity of Technology
%A Dalian Naval Test Base
%A Dalian
%A <br>侯代文
%A 殷福亮
%A 陈喆
%J 自动化学报
%D 2009
%I 
%X A mean shift quasi-Monte Carlo (MS-QMC) method is proposed for speaker tracking. To explore the state space more efficiently, deterministic samplers are used instead of random draws according to a quasi-Monte Carlo integration rule in the new method. Furthermore, a mean shift procedure is applied to move particles toward the modes of the posterior, leading to a more effective allocation of particles thereupon fewer particles are needed. Simulation results show that compared with the traditional particle filter, both speaker tracking accuracy and convergent rate of the proposed method are improved.
%K Speaker tracking
%K quasi-Monte Carlo (QMC) filtering
%K particle filter
%K mean shift (MS)
%K state estimation<br>说话人跟踪
%K 拟蒙特卡洛滤波
%K 粒子滤波
%K 均值漂移
%K 状态估计
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=D5035E3CC4E9E2EA53FBFC4924FCF6BD&yid=DE12191FBD62783C&vid=6209D9E8050195F5&iid=DF92D298D3FF1E6E&sid=7AD2D1CE7CD34BB7&eid=5D5B6851F9BAEE73&journal_id=0254-4156&journal_name=自动化学报&referenced_num=1&reference_num=0