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Gaze and Eye Tracking: Techniques and Applications in ADAS

期刊

SENSORS
卷 19, 期 24, 页码 -

出版社

MDPI
DOI: 10.3390/s19245540

关键词

advanced driving assistance systems (ADAS); eye tracking; gaze tracking; line of sight (LoS); point of regard (PoR); road safety

资金

  1. 3D Recognition Project of Korea Evaluation Institute of Industrial Technology (KEIT) [10060160]
  2. Robocarechair: A Smart Transformable Robot for Multi-Functional Assistive Personal Care Project of KEIT [P0006886]
  3. e-Drive Train Platform Development for Commercial Electric Vehicles based on IoT Technology Project of Korea Institute of Energy Technology Evaluation and Planning (KETEP) - Korean Ministry of Trade, Industry and Energy (MOTIE) [20172010000420]
  4. Institute of Information and Communication Technology Planning AMP
  5. Evaluation (IITP) - Korean Ministry of Science and Information Technology (MSIT) [2019-0-00421]
  6. Institute for Information & Communication Technology Planning & Evaluation (IITP), Republic of Korea [2019-0-00421-001] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  7. Korea Evaluation Institute of Industrial Technology (KEIT) [20172010000420] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

Tracking drivers' eyes and gazes is a topic of great interest in the research of advanced driving assistance systems (ADAS). It is especially a matter of serious discussion among the road safety researchers' community, as visual distraction is considered among the major causes of road accidents. In this paper, techniques for eye and gaze tracking are first comprehensively reviewed while discussing their major categories. The advantages and limitations of each category are explained with respect to their requirements and practical uses. In another section of the paper, the applications of eyes and gaze tracking systems in ADAS are discussed. The process of acquisition of driver's eyes and gaze data and the algorithms used to process this data are explained. It is explained how the data related to a driver's eyes and gaze can be used in ADAS to reduce the losses associated with road accidents occurring due to visual distraction of the driver. A discussion on the required features of current and future eye and gaze trackers is also presented.

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