4.7 Article

In the eye of the beholder: A survey of gaze tracking techniques

期刊

PATTERN RECOGNITION
卷 132, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2022.108944

关键词

Gaze estimation; eye features; appearance -based; personal calibration; head motion

资金

  1. National Key Research and Development Program of China [2018YFC2001700]
  2. Beijing Municipal Natural Science Foundation [4212023]
  3. Scientific and Technological Innovation Foundation of Shunde Graduate School, USTB
  4. Foundation of Engineering Research Center of Intelligence Perception and Autonomous Control, Ministry of Education, P. R. China
  5. Fundamental Research Funds for the Central Universities [FRF-GF-20-04A]

向作者/读者索取更多资源

This paper introduces the visual information and commonly used estimation methods in gaze tracking, discusses key issues and research trends, and compares the characteristics of these methods. The applications of gaze tracking techniques in different fields are also analyzed.
Gaze tracking estimates and tracks the user's gaze by analyzing facial or eye features, it is an important way to realize automated vision-based interaction. This paper introduces the visual information used in gaze tracking, and discusses the commonly used gaze estimation methods and their research dynamics, including: 2D mapping-based methods, 3D model-based methods, and appearance-based methods. In this way, some key issues that need to be solved in these methods are considered, and their research trends are discussed. Their characteristics in system configuration, personal calibration, head motion, gaze accu-racy and robustness are also compared. Finally, the applications of gaze tracking techniques are analyzed from various application factors and fields. This paper reviews the latest development of gaze tracking, focuses more on various gaze tracking algorithms and their existing challenges. The development trends of gaze tracking are prospected, which provides ideas for future theoretical research and practical appli-cations. (c) 2022 Elsevier Ltd. All rights reserved.

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