首页 | 本学科首页   官方微博 | 高级检索  
     

共享隐变量模型的解析算法及应用
引用本文:仝明磊,边后琴.共享隐变量模型的解析算法及应用[J].上海电力学院学报,2010,26(5):478-480,497.
作者姓名:仝明磊  边后琴
作者单位:上海电力学院计算机与信息工程学院,上海200090
基金项目:上海电力学院实验教改项目
摘    要:从理论上探讨了共享隐结构模型的实质,并证明其与经典主分量分析的等价性.针对经典的共享隐结构算法需要使用确定性优化算法或者EM算法求解、且初值的设定以及优化速度精度很难控制这一特点,给出了共享隐变量模型的解析式,证明了高斯过程共享隐变量模型等价于经典PCA方法,即可以用PCA方法作为共享隐变量模型的解析式,并给出在人体运动分析中的实验结果.

关 键 词:共享隐变量模型  三维人体运动分析  维数约简
收稿时间:2010/7/12 0:00:00

Close Form Algorithm of Shared Latent Model and Its Application
TONG Ming-lei and BIAN Hou-qin.Close Form Algorithm of Shared Latent Model and Its Application[J].Journal of Shanghai University of Electric Power,2010,26(5):478-480,497.
Authors:TONG Ming-lei and BIAN Hou-qin
Affiliation:(School of Computer and Information Engineering,Shanghai University of Electric Power,Shanghai 200090,China)
Abstract:The characteristics of the Shared Latent Model are studied from theoretical perspective with focus on the lack of a closed-form solution for the shared latent model,and proof is given that the Principal Component Analysis is equivalent to the shared latent model.Furthermore,ridge regression is introduced to the framework of calculating shared latent model.Finally,the experimental results are presented to prove the efficiency of the algorithm.
Keywords:shared latent model  3D human motion  dimensions reduction
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《上海电力学院学报》浏览原始摘要信息
点击此处可从《上海电力学院学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号