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Intelligent Gesture Recognition Based on Screen Reflectance Multi-Band Spectral Features.

Peiying Lin¹, Chenrui Li², Sijie Chen²

¹School of Electrical and Information Engineering, Jiangsu University of Science and Technology, Zhangjiagang 215600, China.

Sensors (Basel, Switzerland)

|September 14, 2024

Summary

This summary is machine-generated.

This study introduces a novel gesture recognition system using screen-reflected light and spectral features. The system achieves high accuracy for human-computer interaction (HCI) across various lighting conditions.

Keywords:

gesture recognition human–computer interaction multi-band spectra

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Area of Science:

Human-Computer Interaction (HCI)
Computer Vision
Signal Processing

Background:

Digitalization trends emphasize intuitive human-computer interaction (HCI) methods.
Gesture recognition via screens is a key area for advancing HCI.
Existing methods may face challenges with varying environmental lighting.

Purpose of the Study:

To propose a novel gesture recognition method combining spectral and spatial features.
To develop an RGB three-channel spectral gesture recognition system.
To enhance the accuracy and stability of gesture recognition for HCI.

Main Methods:

Utilizing multi-band spectral features and spatial characteristics of screen-reflected light.
Developing a system with a display screen and narrowband spectral receivers.
Formulating an RGB multi-channel convolutional neural network long short-term memory (CNN-LSTM) model.

Main Results:

Achieved 99.93% accuracy in darkness and 99.89% in illuminated conditions.
Demonstrated stable and accurate gesture recognition across different lighting environments.
Integrated multidimensional features from frequency and spatial domains for enhanced classification.

Conclusions:

The proposed spectral gesture recognition method offers high accuracy and stability.
The developed RGB CNN-LSTM model is effective for gesture-based HCI.
This intelligent method has broad applications for interactive screens like computers and mobile devices.