Early gesture recognition with adaptive window selection employing canonical correlation analysis for gaming

A new early gesture recognition system that uses different features obtained from MYO sensor is presented. The beginning part of each gesture is detected and used by the system to train the authors’ recognition algorithm. To preserve the different features temporal alignment for each movement, two-d...

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Bibliographic Details
Published in:Electronics letters 2016-08, Vol.52 (16), p.1379-1381
Main Authors: El-Shazly, E.H, Abdelwahab, M. M, Shimada, A, Taniguchi, R
Format: Article
Language:English
Subjects:
adaptive window selection
Algorithms
author recognition algorithm
canonical correlation analysis for gaming
CCA
computer games
Correlation analysis
correlation methods
early gesture recognition system
Electronics
feature extraction
feature temporal alignment
gesture detection
gesture recognition
Image and vision processing and display technology
image matching
image sensors
MYO sensor
Preserves
principal component analysis
processing complexity
Projection
real‐time implementation
Recognition
testing pairs
testing sequence
Training
Two dimensional
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Description
Summary:A new early gesture recognition system that uses different features obtained from MYO sensor is presented. The beginning part of each gesture is detected and used by the system to train the authors’ recognition algorithm. To preserve the different features temporal alignment for each movement, two-dimensional (2D) principal component analysis was employed to obtain the dominant features by processing the obtained data in its 2D form. Canonical correlation analysis (CCA) is used to find a space where the projection of similar training testing pairs becomes highly correlated. Finally, the testing sequence is matched to the training set that gives maximum correlation in the new space obtained by CCA. Low processing complexity, storage requirement, accurate and fast decision obtained on the newly collected data set are factors that promotes the authors’ algorithm for real-time implementation.
ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2016.1540