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

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.
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