Oculang: Empowering Communication through Blink Language Detection

Oculang is a communication system that uses computer vision and machine learning techniques to enable individuals with neurodegenerative disorders to communicate using eye gestures. The application focuses on detecting facial landmarks, gaze estimation, and blink detection to analyze combinations of eye movements captured from video input and produce message outputs. Dlib’s shape predictor (68 facial landmarks) and OpenCV-based image processing methods are used to extract and process the features of the eye region. A decision-making algorithm maps the detected gestures and predefined keywords for message generation. The application supports both real-time video capturing and uploading video through a Django-based user interface. Experimental evaluation on recorded datasets of eye movements demonstrated robust performance in accurately recognizing blinks, winks, and gaze directions, validating the system’s reliability.

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Publication Details

Journal
IRO Journal on Sustainable Wireless Systems
Published
2025-01-22
DOI
https://doi.org/10.36548/jsws.2024.4.003
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
0.00
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article

Oculang: Empowering Communication through Blink Language Detection

R Harshada, S. Suriya, V S Anubharathi, G Bharathi et al.
IRO Journal on Sustainable Wireless Systems
Gaze Tracking and Assistive Technology
article

Oculang: Empowering Communication through Blink Language Detection

R Harshada, S. Suriya, V S Anubharathi, G Bharathi, Vignesh Aditya R, B G Sundarsree
article en

Abstract

Oculang is a communication system that uses computer vision and machine learning techniques to enable individuals with neurodegenerative disorders to communicate using eye gestures. The application focuses on detecting facial landmarks, gaze estimation, and blink detection to analyze combinations of eye movements captured from video input and produce message outputs. Dlib’s shape predictor (68 facial landmarks) and OpenCV-based image processing methods are used to extract and process the features of the eye region. A decision-making algorithm maps the detected gestures and predefined keywords for message generation. The application supports both real-time video capturing and uploading video through a Django-based user interface. Experimental evaluation on recorded datasets of eye movements demonstrated robust performance in accurately recognizing blinks, winks, and gaze directions, validating the system’s reliability.

IRO Journal on Sustainable Wireless SystemsVol. 6(4)
PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN)
Openalex Percentile: Top 99%
Gaze Tracking and Assistive Technology
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Oculang: Empowering Communication through Blink Language Detection — R Harshada, S. Suriya, et al. · IRO Journal on Sustainable Wireless Systems (2025) | TGRS Research Map | TGRS