中国科学院苏州纳米技术与纳米仿生研究所机构知识库
Advanced  
SINANO OpenIR  > 系统集成与IC设计部  > 张耀辉团队  > 期刊论文
题名: Supervised sparse manifold regression for head pose estimation in 3D space
作者: Wang, QC; Wu, YX; Shen, YH(沈晔湖); Liu, Y; Lei, YQ
通讯作者: Lei, YQ
关键词: Manifold learning ; Supervised learning ; Sparse regression ; Head pose estimation
刊名: SIGNAL PROCESSING
发表日期: 2015
DOI: 10.1016/j.sigpro.2014.07.011
卷: 112, 页:9
收录类别: SCI
部门归属: 系统集成与IC设计部
英文摘要: In estimating the head pose angles in 3D space by manifold learning, the results currently are not very satisfactory. We need to preserve the local geometry structure effectively and need a learned projective function that can reveal the dominant features better. To address these problems, we propose a Supervised Sparse Manifold Regression (SSMR) method that incorporates both the supervised graph Laplacian regularization and the sparse regression into manifold learning. In SSMR, on the one hand, a low-dimensional projection is embedded to represent intrinsic features by using supervised information while the local structure can be preserved more effectively by using the Laplacian regularization term in the objective function. On the other hand, by casting the problem of learning projective function into a regression with L-1 norm regularizer, a projection is mapped to carry out the sparse representation of high dimension features, rather than a compact linear combination, so as to describe the dominant features better. Experiments show that our proposed method SSMR is beneficial for head pose angle estimation in 3D space. (C) 2014 Elsevier B.V. All rights reserved.
语种: 英语
JCR小类分区: 三区
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.sinano.ac.cn/handle/332007/3349
Appears in Collections:系统集成与IC设计部_张耀辉团队_期刊论文

Files in This Item:
File Name/ File Size Content Type Version Access License
Supervised sparse manifold regression for head pose estimation in 3D space.pdf(866KB)期刊论文作者接受稿限制开放View 联系获取全文

Recommended Citation:
Wang, QC,Wu, YX,Shen, YH,et al. Supervised sparse manifold regression for head pose estimation in 3D space[J]. SIGNAL PROCESSING,2015,112:9.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Wang, QC]'s Articles
[Wu, YX]'s Articles
[Shen, YH(沈晔湖)]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Wang, QC]‘s Articles
[Wu, YX]‘s Articles
[Shen, YH(沈晔湖)]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: Supervised sparse manifold regression for head pose estimation in 3D space.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!