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A review and analysis of eye-gaze estimation systems, algorithms and performance evaluation methods in consumer platforms

Kar, Anuradha
; 
Corcoran, Peter
Identifiers
http://hdl.handle.net/10379/12146
https://doi.org/10.13025/28119
Repository DOI
10.1109/access.2017.2735633
Publication Date
2017-01-01
Keywords
eye gaze, gaze estimation, accuracy, error sources, performance evaluation, user platforms, real-time eye, driver visual-attention, multiple light-sources, head-mounted camera, tracking system, single-camera, computer-interface, pupil detection, neural-network, calibration
Type
Article
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Citation
Kar, Anuradha; Corcoran, Peter (2017). A review and analysis of eye-gaze estimation systems, algorithms and performance evaluation methods in consumer platforms. IEEE Access 5 , 16495-16519
Abstract
In this paper, a review is presented for the research on eye gaze estimation techniques and applications, which 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 the 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.
Funder
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publisher DOI
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Externally hosted open access publications with University of Galway authors (2)