A real-time gesture recognition system using near-infrared imagery

Visual hand gesture recognition systems are promising technologies for Human Computer Interaction, as they allow a more immersive and intuitive interaction. Most of these systems are based on the analysis of skeleton information, which is in turn inferred from color, depth, or near-infrared imagery....

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Bibliographic Details
Published in:PloS one 2019-10, Vol.14 (10), p.e0223320-e0223320
Main Authors: Mantecón, Tomás, Del-Blanco, Carlos R, Jaureguizar, Fernando, García, Narciso
Format: Article
Language:English
Subjects:
Advantages
Analysis
Biology and Life Sciences
Cameras
Color imagery
Engineering and Technology
Gesture recognition
Gestures
Hand
Health aspects
Human-computer interaction
Humans
I.R. radiation
Image processing
Image Processing, Computer-Assisted
Information processing
Infrared analysis
Infrared imagery
Medicine and Health Sciences
Mental task performance
Near-infrared spectroscopy
Optical Imaging - methods
Pattern recognition
Pattern Recognition, Automated - methods
Physical sciences
Real time
Real time systems
Recognition
Recognition, Psychology
Research and Analysis Methods
Sensors
Sign language
Signal processing
Skeleton
Social Sciences
Technology
Unmanned aerial vehicles
Visual system
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Summary:Visual hand gesture recognition systems are promising technologies for Human Computer Interaction, as they allow a more immersive and intuitive interaction. Most of these systems are based on the analysis of skeleton information, which is in turn inferred from color, depth, or near-infrared imagery. However, the robust extraction of skeleton information from images is only possible for a subset of hand poses, which restricts the range of gestures that can be recognized. In this paper, a real-time hand gesture recognition system based on a near-infrared device is presented, which directly analyzes the infrared imagery to infer static and dynamic gestures, without using skeleton information. Thus, a much wider range of hand gestures can be recognized in comparison with skeleton-based approaches. To validate the proposed system, a new dataset of near-infrared imagery has been created, from which good results that outperform other state-of-the-art strategies have been obtained.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0223320