# Gaze Error Estimation and Linear Transformation to Improve Accuracy of Video-Based Eye Trackers

## TL;DR

This paper introduces a method to enhance the accuracy of eye tracking systems using linear transformations.

## Contribution

The novel contribution is the use of linear coordinate transformations to correct gaze errors in video-based eye trackers.

## Key findings

- Linear transformations significantly improve gaze accuracy over a large field of view.
- The method involves stretching, shearing, and translating coordinates to correct errors.

## Abstract

Eye tracking technology plays a crucial role in various fields such as psychology, medical training, marketing, and human–computer interaction. However, achieving high accuracy over a larger field of view in eye tracking systems remains a significant challenge, both in free viewing and in a head-stabilized condition. In this paper, we propose a simple approach to improve the accuracy of video-based eye trackers through the implementation of linear coordinate transformations. This method involves applying stretching, shearing, translation, or their combinations to correct gaze accuracy errors. Our investigation shows that re-calibrating the eye tracker via linear transformations significantly improves the accuracy of video-based tracker over a large field of view.