International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
www.irjet.net
TOUCHLESS EYE HAND CONTROL (TEHC) - Unified Control with Eye and Hand Interface Mrs. Bhuvaneswari1, Kiran Kumar2, Nandhan3 , Adithya4, Aravind Amarnath5 1Professor of Department of Information Technology, Meenakshi College of Engineering, Chennai, Tamil Nadu,
India
2,3,4,5 Student of Department of Information Technology, Meenakshi College of Engineering, Chennai, Tamil Nadu,
India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Touchless eye-hand control (TEHC) refers to the
Moreover, the proposed TEHC system aims to deliver an interactive user interface with minimal response lag time, ensuring a seamless user experience. The system's design prioritizes simplicity and convenience, making it accessible and easy to use for individuals with disabilities in operating computers and interacting with digital objects. Through the integration of advanced HCI techniques, TEHC represents a significant step forward in enhancing computer accessibility and empowering disabled individuals to engage more fully in computer-based tasks.
use of eye and hand movements to interact with digital devices without physically touching them. This technology has the potential to revolutionize the way we interact with devices, especially for people with physical disabilities. Python and OpenCV library are utilized for real-time computer vision implementation, with the camera output displayed on the monitor. Integrating advanced computer vision, it enables precise cursor control without physical contact, through eye tracking and hand gesture recognition. Despite challenges, including accuracy and environmental factors, TEHC holds promise for gaming, communication, and virtual reality applications.
1.1 Existing System In their innovative system, the researchers employed a Convolutional Neural Network (CNN) for face detection, achieving high accuracy in identifying and localizing faces within images. This initial step laid a robust foundation for subsequent analysis. Building upon this foundation, a YOLOv4-based object detection framework was integrated into the system, enabling precise and reliable face recognition. This framework ensured the system's adaptability to various environmental conditions, enhancing its effectiveness in real-world scenarios.
Key Words: TEHC, Eye-hand gesture recognition, Physical disabilities, Cursor control.
1.INTRODUCTION Human-computer interaction (HCI) has undergone significant advancements in recent years, particularly in making computers more accessible to individuals with restricted motor abilities. Prior research has yielded various devices aimed at assisting disabled individuals using gestures and other non-contact techniques. However, many HCI activities still require user interaction without relying on an assistant or assistive device, which poses challenges for those with limited motor skills such as spinal cord injuries and limb paralysis. HCI plays a crucial role in providing opportunities for disabled individuals to engage in computer-based tasks, including cursor control.
Once faces were detected and recognized, the system utilized the estimated head pose and captured facial area to facilitate cursor movement control. By interpreting subtle head movements and facial cues, users could intuitively manipulate the cursor on the screen, providing a natural interaction method. This seamless integration of head pose estimation and facial analysis contributed to a user-friendly experience, particularly beneficial for individuals with restricted motor abilities.
This paper proposes the development of a Touchless EyeHand Control (TEHC) system designed to enhance computer accessibility for individuals with disabilities. TEHC utilizes eye tracking and hand gesture recognition to control the cursor on a personal computer. By accurately estimating the user's eye position and tracking head/face movements, including nodding for vertical movement and rotation for horizontal movement, the system enables precise cursor control without physical contact. Additionally, mouse button functions are activated by bending the head left or right, providing further control flexibility.
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To further enhance cursor tracking precision, the researchers incorporated a Kalman filter into the system. This filter refined the trajectory of the cursor, smoothing its movements and reducing jitter or inaccuracies. Continuously adjusting the cursor's predicted position based on incoming data, the Kalman filter ensured responsive and accurate cursor control, ultimately optimizing the overall user experience.
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