NDLI: Calibration of kinematic body sensor networks: Kinect-based gauging of data gloves “in the wild”

Content Provider	IEEE Xplore Digital Library
Author	Vicente, Alexandre P. Faisal, A. Aldo
Copyright Year	2013
Description	Author affiliation: Department of Computing, Imperial College London (Vicente, Alexandre P.) \|\| Dept. of Bioengineering & Dept. of Computing, Imperial College London & MRC Clinical Sciences Center, London, UK (Faisal, A. Aldo)
Abstract	Our hands generic precision and agility is yet unmatched by technology, hence the quantitative study of its daily life kinematics is fundamental to neurology/prosthetics & robotics and creative industries. State-of-the-art solutions capturing hand movements ‘in the wild’ requires wearable body sensor networks: data gloves. Yet, fast-accurate calibration is challenging due to variability in hand anatomy and complexity of finger joints. We present here novel methods for calibration using streaming information from depth cameras (Microsoft Kinect). Our low-cost system calibrates the data glove by observing a user wiggling their hands while wearing data gloves. Using inverse kinematics we reconstruct in real-time hand configuration, enabling augmented reality by superimposing the virtual and real hand veridically. We achieve accuracies of ±5 degrees RMSE over all 21 joints, almost 20% more accurate than standard calibration methods and accurately capture touching of fingertips and thumb — our benchmark test unmatched by other calibration methods.
Starting Page	1
Ending Page	6
File Size	1274692
Page Count	6
File Format	PDF
ISBN	9781479903313
ISSN	23251433
e-ISBN	9781479903306
DOI	10.1109/BSN.2013.6575526
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Thumb Kinematics Data gloves Bones Calibration Sensors Joints
Content Type	Text
Resource Type	Article

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