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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
Source Publication自动化学报
Indexed ByEI ; CSCD
EI Accession number20170403278969
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
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.
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Document Type期刊论文
Corresponding Author杜惠斌
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.
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