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Advances in Eye Tracking Technology: Theory, Algorithms, and Applications
Author(s) -
Hong Fu,
Ying Wei,
Francesco Camastra,
Pietro Aricò,
Hong Sheng
Publication year - 2016
Publication title -
computational intelligence and neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.605
H-Index - 52
eISSN - 1687-5273
pISSN - 1687-5265
DOI - 10.1155/2016/7831469
Subject(s) - computer science , eye tracking , gaze , computer vision , tracking (education) , virtual reality , artificial intelligence , eye movement , match moving , table (database) , stability (learning theory) , human–computer interaction , motion (physics) , machine learning , psychology , data mining , pedagogy
The goal of eye tracking is to detect and measure the point of gaze (where one is looking) or the motion of eye(s) relative to the head. The eye tracking data obtained by an eye tracker provide new opportunities and potentials in a broad range of applications including human computer interaction, computer simulation/virtual reality, neuroscience, medical, and cognitive-behavioral research. In recent years, eye tracking technology has been undergoing rapid development with improvements in the accuracy, stability, and sampling rates. A number of technologies and techniques are now available, including head-mounted, glass, table-mounted, and embedded systems, and with these advances new opportunities and applications are emerging. This special issue aims to bring together theoretical and practical perspectives in the area of eye tracking technology to present and discuss the latest technological developments and to inspire interaction and creation.

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