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Eye Gaze Detection

Eye tracking and gaze detection for monitoring the attentiveness and stress levels.

What is Eye Gaze Detection?

Eye gaze detection uses image recognition with deep learning to perform eye tracking. Gaze tracking is typically employed to determine a person’s focus of attention.

Eye tracking is becoming a very important capability across many domains, including security, psychology, computer vision, and medical diagnosis. Also, gaze is important for security applications to analyze suspicious gaze behavior. A use case in educational institutes is the automated analysis of the student’s eye gazes during an examination to help minimize malpractices.

Features of Real-time Eye Gaze Tracking

Real-time eye tracking and eye gazing estimation using deep neural networks. Modern Edge Computer Vision with powerful on-device machine learning allows large-scale eye-tracking for gaze-based analysis.

  • Face detection for finding faces.
  • Head pose estimation to provide input for gaze estimation model.
  • Facial landmarks for detected faces with keypoints to locate the eyes regions.
  • Eye state detection in detected faces (open, closed).
  • Real-time video input from surveillance cameras or webcams/USB cameras.
  • Edge AI processing allows privacy-preserving on-device computing that is robust (online/offline).

Value of Eye Gaze Estimation Systems with Deep Learning

Eye tracking is still a novel technology that requires adequate computing resources. However, with recent advances in deep learning and edge AI, high accuracy can be achieved without the need for complex hardware. Hence, eye tracking is becoming available to use in a wide range of real-world use cases.

  • Large-scale implementation: No burdensome explicit user calibration. Modern deep learning models are much more robust than prior methods that perform poorly on imperfect image quality and lighting.
  • Increase operational productivity: Automated eye tracking is used as an indicator for stress level and attentiveness analysis. Both factors critically impact the product/service quality.
  • Accident avoidance: Real-time driver monitoring detects distracted driving and gaze distraction from the road (smartphone usage, eating or drinking, and others).
  • Safety systems: Eye gaze tracking is used in robust fatigue detection systems to improve safety in transportation and manufacturing.
  • Cost savings through lower insurance premiums and avoidance of fees and accidents (e.g., ensuring rest breaks of drivers).
Last updated
December 12, 2021
Requires Viso Suite

How to get started

This solution is built on Viso Suite, the all-in-one computer vision platform to deploy, run and scale the solution with powerful tools and infrastructure.

To get started, request a personal demo, we will put together a plan that includes all the services you need to get started.

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