SIA OpenIR  > 机器人学研究室
基于集员滤波的双Kinect人体关节点数据融合
Alternative TitleData Fusion of Human Skeleton Joint Tracking Using Two Kinect Sensors and Extended Set Membership Filter
杜惠斌; 赵忆文; 韩建达; 赵新刚; 王争; 宋国立
Department机器人学研究室
Source Publication自动化学报
ISSN0254-4156
2016
Volume42Issue:12Pages:1886-1898
Indexed ByEI ; CSCD
EI Accession number20170403278969
CSCD IDCSCD:5883874
Contribution Rank1
Funding Organization国家自然科学基金(U1508208), 中科院机器人与智能制造自主部署课题(C2016001)资助
Keyword镜像康复 Kinect深度图像传感器 Bursa线性模型 集员滤波
Abstract以Kinect为代表的深度图像传感器在肢体康复系统中得到广泛应用.单一深度图像传感器采集人体关节点数据时由于肢体遮挡、传感器数据错误和丢失等原因降低系统可靠性.本文研究了利用两台Kinect深度图像传感器进行数据融合从而达到消除遮挡、数据错误和丢失的目的,提高康复系统中数据的稳定性和可靠性.首先,利用两台Kinect采集患者健康侧手臂运动数据;其次,对两组数据做时间对准、Bursa线性模型下的坐标变换和基于集员滤波的数据融合;再次,将融合后的健康侧手臂运动数据经过”镜像运动”作为患侧手臂运动指令;最后,将患侧运动指令下发给可穿戴式镜像康复外骨骼带动患者患侧手臂完成三维动画提示的康复动作,达到患...
Other AbstractKinect-like depth sensors have been widely used in rehabilitation systems. However, single depth sensor processes limb-blocking, data-loss or error poorly, making it less reliable. This paper focus on using two Kinect sensors and data fusion algorithm to solve these problems. First, two Kinect sensors capture the motion data of the healthy side arm of the hemiplegic patient; Second, process the data with time alignment, coordinate transformation with Bursa transform, and data fusion using Extended-Set-Membership-Filter successively; Then, mirror this motion data by the Middle-Plane, namely ”mirror motion”; In the end, this motion data controls the wearable robotic arm driving the patient’s paralytic side arm to interactively and initiatively complete a variety of recovery actions prompted by computer with 3D animation games. The effectiveness of the proposed approach is validated with both experiments on Kinect Sensors & VICON and a 7 DOF manipulator. Also, two Kinect sensors can solve those problems effectively.
Language中文
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/19475
Collection机器人学研究室
Corresponding Author杜惠斌
Affiliation1.中国科学院沈阳自动化研究所机器人学国家重点实验室
2.中国科学院大学
Recommended Citation
GB/T 7714
杜惠斌,赵忆文,韩建达,等. 基于集员滤波的双Kinect人体关节点数据融合[J]. 自动化学报,2016,42(12):1886-1898.
APA 杜惠斌,赵忆文,韩建达,赵新刚,王争,&宋国立.(2016).基于集员滤波的双Kinect人体关节点数据融合.自动化学报,42(12),1886-1898.
MLA 杜惠斌,et al."基于集员滤波的双Kinect人体关节点数据融合".自动化学报 42.12(2016):1886-1898.
Files in This Item: Download All
File Name/Size DocType Version Access License
基于集员滤波的双Kinect人体关节点数(1133KB)期刊论文出版稿开放获取ODC PDDLView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[杜惠斌]'s Articles
[赵忆文]'s Articles
[韩建达]'s Articles
Baidu academic
Similar articles in Baidu academic
[杜惠斌]'s Articles
[赵忆文]'s Articles
[韩建达]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[杜惠斌]'s Articles
[赵忆文]'s Articles
[韩建达]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 基于集员滤波的双Kinect人体关节点数据融合.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

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