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Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching
Joint Authors
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-11
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Hand gesture recognition has become more and more popular in applications like intelligent sensing, robot control, smart guidance, and so on.
In this paper, an inertial sensor based hand gesture recognition method is proposed.
The proposed method obtains the trajectory of the hand by using a position estimator.
The proposed method utilizes the attitude estimation to produce velocity and position estimation.
A particle filter (PF) is employed to estimate the attitude quaternion from gyroscope, accelerometer, and magnetometer sensors.
The improvement is based on the resampling method making the original filter much faster to converge.
After smoothing, the trajectory is then converted to low-definition images which are further sent to a backpropagation neural network (BP-NN) based recognizer for matching.
Experiments on real-world hardware are carried out to show the effectiveness and uniqueness of the proposed method.
Compared with representative methods using accelerometer or vision sensors, the proposed method is proved to be fast, reliable, and accurate.
American Psychological Association (APA)
Wang, Zuocai& Chen, Bin& Wu, Jin. 2018. Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184525
Modern Language Association (MLA)
Wang, Zuocai…[et al.]. Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1184525
American Medical Association (AMA)
Wang, Zuocai& Chen, Bin& Wu, Jin. Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184525
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184525