iMouse – Eye Tracking Application

Ajay Gandhi, Kunal Patil, Reema Deshpande, Geetanjali Nazirkar


Physically handicapped people are unable to perform the basic computer operations. a low-computational approach on gaze estimation is proposed using the Eye Touch system, which is a light-reflection based eye tracking system. Based on the physical implementation of Eye Touch, the sensor measurements are now utilized to estimate arbitrary gaze directions. The system also utilizes an effective pattern classification algorithm to be able to perform left, right, and double clicks based on respective eye winks with significantly high accuracy.


In order to avoid accuracy problems for sensitive sensor biasing hardware, a robust custom microcontroller-based data acquisition system is developed. Consequently, the physical size and cost of the overall Eye Touch system are considerably reduced while the power efficiency is improved. Due to its lightweight structure, competitive accuracy and low-computational requirements relative to video-based eye tracking systems, the proposed system is a promising human-computer interface for both stationary and mobile eye tracking applications.

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