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Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
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VisualEyes: A Modular Software System for Oculomotor Experimentation
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KlugOculus: A Vision-Based Intelligent Architecture for Security System.

Navjot Rathour1, Rajesh Singh1, Anita Gehlot1

  • 1Division of Research & Innovation, Uttaranchal University, Dehradun, Uttarakhand 248007, India.

Computational Intelligence and Neuroscience
|May 27, 2022
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Summary
This summary is machine-generated.

This study introduces a vision-based system for intruder detection using facial recognition. The proposed architecture achieves 99.9% accuracy, enhancing security systems with reliable identification capabilities.

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Security Systems

Background:

  • Traditional security systems face limitations in computational power for real-time facial recognition.
  • Adaptive video analytics and machine learning are emerging for enhanced activity detection.

Purpose of the Study:

  • To propose a vision-based intelligent architecture for intruder detection using facial recognition.
  • To develop a system with customized hardware for improved security applications.

Main Methods:

  • Facial recognition implemented using machine learning (ML) inspired Support Vector Machine (SVM) and Histogram of Oriented Gradients (HOG).
  • System trained with 120 images across 20 subjects.
  • Real-time implementation on Raspberry Pi 3 hardware.

Main Results:

  • Achieved 99.9% accuracy in intruder identification for 20 subjects.
  • Demonstrated high accuracy (99.9%) even with tilted subject images.
  • Successful real-time facial recognition on embedded hardware.

Conclusions:

  • The proposed vision-based system offers a highly accurate and robust solution for intruder detection.
  • The system's performance, even with image variations, makes it suitable for adoption by security personnel.
  • This technology can significantly boost existing security infrastructure for identification purposes.