Journal ArticleDOI
MEMS Accelerometer Based Nonspecific-User Hand Gesture Recognition
Ruize Xu,Shengli Zhou,Wen J. Li +2 more
TLDR
A recognition algorithm based on sign sequence and template matching as presented in this paper can be used for nonspecific-users hand-gesture recognition without the time consuming user-training process prior to gesture recognition.Abstract:
This paper presents three different gesture recognition models which are capable of recognizing seven hand gestures, i.e., up, down, left, right, tick, circle, and cross, based on the input signals from MEMS 3-axes accelerometers. The accelerations of a hand in motion in three perpendicular directions are detected by three accelerometers respectively and transmitted to a PC via Bluetooth wireless protocol. An automatic gesture segmentation algorithm is developed to identify individual gestures in a sequence. To compress data and to minimize the influence of variations resulted from gestures made by different users, a basic feature based on sign sequence of gesture acceleration is extracted. This method reduces hundreds of data values of a single gesture to a gesture code of 8 numbers. Finally, the gesture is recognized by comparing the gesture code with the stored templates. Results based on 72 experiments, each containing a sequence of hand gestures (totaling 628 gestures), show that the best of the three models discussed in this paper achieves an overall recognition accuracy of 95.6%, with the correct recognition accuracy of each gesture ranging from 91% to 100%. We conclude that a recognition algorithm based on sign sequence and template matching as presented in this paper can be used for nonspecific-users hand-gesture recognition without the time consuming user-training process prior to gesture recognition.read more
Citations
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Hand Gesture Recognition Techniques for a Wireless Robotic Arm using Calculus
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Mixed Nonlinear Response and Transition of Nonlinearity in a Piezoelectric Membrane
TL;DR: In this paper , the impact of fabrication-induced curvature on the dynamics of zinc oxide-based piezoelectric micromachined ultrasonic transducers (PMUTs) was investigated.
Wearable technology and gesture recognition for live performance augmentation
TL;DR: Although the system did not fully live up to design objectives, it plays the role of an important stepping stone in the creation of practical, entertainment-oriented gesture recognition devices that are more accessible to the general public.
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Map modeling for full body gesture using flex sensor and machine learning algorithms
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Noise behaviors of a closed-loop micro-electromechanical system capacitive accelerometer
TL;DR: In this paper, a thorough noise analysis is established focusing on the four noise sources transfer functions near 0 Hz with simplified electronic parameters in closed loop, and it is found that the total electronic noise equivalent acceleration varies differently at different frequency points, such that the noise spectrum shape at low frequencies can be altered from 1/f noise-like shape to flat spectrum shape.
References
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Pattern Recognition and Machine Learning
TL;DR: Probability Distributions, linear models for Regression, Linear Models for Classification, Neural Networks, Graphical Models, Mixture Models and EM, Sampling Methods, Continuous Latent Variables, Sequential Data are studied.
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Pattern Recognition and Machine Learning
TL;DR: This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.
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TL;DR: The principles of interactive computer graphics are discussed in this article, where the authors propose a set of principles for the development of computer graphics systems, including the principles of Interactive Computer Graphics (ICG).
Proceedings ArticleDOI
Gesture recognition with a Wii controller
TL;DR: The design and evaluation of the sensor-based gesture recognition system is presented, which allows the training of arbitrary gestures by users which can then be recalled for interacting with systems like photo browsing on a home TV.
Journal ArticleDOI
Glove-Talk: a neural network interface between a data-glove and a speech synthesizer
Sidney Fels,Geoffrey E. Hinton +1 more
TL;DR: To illustrate the potential of multilayer neural networks for adaptive interfaces, a VPL Data-Glove connected to a DECtalk speech synthesizer via five neural networks was used to implement a hand-gesture to speech system, demonstrating that neural networks can be used to develop the complex mappings required in a high bandwidth interface that adapts to the individual user.