A Review and Analysis of Eye-Gaze Estimation Systems, Algorithms and Performance Evaluation Methods in Consumer Platforms

TL;DR

This paper reviews two decades of research on eye-gaze estimation systems across various consumer platforms, highlighting the need for standardized evaluation methods and proposing a framework for consistent performance assessment.

Contribution

It provides a comprehensive review of existing eye-gaze estimation techniques and introduces a methodological framework for standardized performance evaluation.

Findings

Identification of platform-specific factors affecting accuracy

Recognition of the lack of standardized evaluation methods

Proposal of a new framework for performance assessment

Abstract

In this paper a review is presented of the research on eye gaze estimation techniques and applications, that has progressed in diverse ways over the past two decades. Several generic eye gaze use-cases are identified: desktop, TV, head-mounted, automotive and handheld devices. Analysis of the literature leads to the identification of several platform specific factors that influence gaze tracking accuracy. A key outcome from this review is the realization of a need to develop standardized methodologies for performance evaluation of gaze tracking systems and achieve consistency in their specification and comparative evaluation. To address this need, the concept of a methodological framework for practical evaluation of different gaze tracking systems is proposed.