求高手帮忙核实论文是否被EI检索？

　　求高手帮忙核实论文是否被EI检索？。第一篇：Model-based Golf Swing Reconstruction
第二篇：Orientation Estimation for Motion Capture Unit with Significant Motion Interference
求高手帮忙查看是否被ei检索。没有找到免费账户。学校图书馆也没有入口。谢谢啦。
===有问必答===
Accession number:20141217498339

Title:Model-based golf swing reconstruction
Authors:Lv, Dong Yue1, 2 ; Huang, Zhi Pei2 ; Sun, Li Xin2; Yu, Neng Hai1; Wu, Jian Kang2
Author affiliation:1 Institution of Electronics, Chinese Academy of Sciences, Beijing, 100190, China
2 University of Chinese Academy of Sciences, Beijing, 100190, China
Source title:Applied Mechanics and Materials
Abbreviated source title:Appl. Mech. Mater.
Volume:530-531
Monograph title:Advances in Measurements and Information Technologies
Issue date:2014
Publication year:2014
Pages:919-927
Language:English
ISSN:16609336
E-ISSN:16627482
ISBN-13:9783038350392
Document type:Conference article (CA)
Conference name:2014 International Conference on Sensors Instrument and Information Technology, ICSIIT 2014
Conference date:January 18, 2014 - January 19, 2014
Conference location:Guangzhou, China
Conference code:103218
Publisher:Trans Tech Publications
Abstract:To increase the efficiency of golf training, 3D swing reconstruction is broadly used among golf researchers. Traditional reconstruction methods apply motion capture system (MOCAP) to gain golfers motion data and drive bio-mechanical model directly. The cost of MOCAP system restricts the application area of golf research and the reconstruction quality of swing relies on the accuracy of the motion data. We introduced the dynamical analysis into swing reconstruction and proposed a Dynamic Bayesian Network (DBN) model with Kinect to capture the swing motion. Our model focused on modeling the bio-mechanical and dynamical relationships between key joints of golfer during swing. The positions of key joints were updated by the model and were used as motion data to reconstruct golf swing. Experimental results show that our results are comparable with the ones acquired by optical MOCAP system in accuracy and can reconstruct the golf swing with much lower cost. copy; (2014) Trans Tech Publications, Switzerland.
Number of references:15
Main heading:SportS
Controlled terms:Digital storage-Information technology
Uncontrolled terms:Bio-mechanical models-Dynamic Bayesian networks-Dynamical analysis-Golf swing-Kinect-Motion capture system-Reconstruction method-Reconstruction quality
Classification code:461.3 Biomechanics, Bionics and Biomimetics -722.1 Data Storage, Equipment and Techniques -903 Information Science
DOI:10.4028/
Database:Compendex
Compilation and indexing terms, copy; 2015 Elsevier Inc.
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Accession number:20141217498186

Title:Orientation estimation for motion capture unit with significant motion interference
Authors:Tian, Ling Tong1 ; Huang, Zhi Pei1; Sun, Yi1; Ji, Lian Ying1; Tao, Guan Hong1
Author affiliation:1 University of Chinese Academy of Sciences, 380 HuaiBei Town, HuaiRou District, Beijing, China
Source title:Applied Mechanics and Materials
Abbreviated source title:Appl. Mech. Mater.
Volume:530-531
Monograph title:Advances in Measurements and Information Technologies
Issue date:2014
Publication year:2014
Pages:155-159
Language:English
ISSN:16609336
E-ISSN:16627482
ISBN-13:9783038350392
Document type:Conference article (CA)
Conference name:2014 International Conference on Sensors Instrument and Information Technology, ICSIIT 2014
Conference date:January 18, 2014 - January 19, 2014
Conference location:Guangzhou, China
Conference code:103218
Publisher:Trans Tech Publications
Abstract:The orientation estimation is a critical technique in inertial sensor based motion capture systems. One challenge of the orientation estimation is that it suffers from the acceleration interference due to body segment motion, especially when the acceleration interference is significant. In this paper, we propose a quaternion based orientation estimation algorithm using unscented Kalman filter. In the algorithm, the acceleration interference is taken as an element of the state vector and estimated in the algorithm together with the orientation quaternion, knowing that the acceleration interference can be predicted based on the rotational angular velocity. The experiments were conducted using both computer simulation and in real-world motion scenarios. Both experimental results have shown the effectiveness of the proposed orientation estimation algorithm. copy; (2014) Trans Tech Publications, Switzerland.
Number of references:6
Main heading:Estimation
Controlled terms:Acceleration-Algorithms-Computer simulation-Information technology-Kalman filters
Uncontrolled terms:Body segment-Critical technique-Inertial sensor-Motion capture-Motion capture system-Motion capture units-Orientation estimation-Unscented Kalman Filter
Classification code:723.5 Computer Applications -731.1 Control Systems -921 Mathematics -931.1 Mechanics
DOI:10.4028/
Database:Compendex
Compilation and indexing terms, copy; 2015 Elsevier Inc.
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