Human Gaze Assisted Artificial Intelligence: A Review

Ruohan Zhang, Akanksha Saran, Bo Liu, Yifeng Zhu, Sihang Guo, Scott Niekum, Dana Ballard, Mary Hayhoe

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Survey track. Pages 4951-4958.

https://doi.org/10.24963/ijcai.2020/689

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Abstract

Human gaze reveals a wealth of information about internal cognitive state. Thus, gaze-related research has significantly increased in computer vision, natural language processing, decision learning, and robotics in recent years. We provide a high-level overview of the research efforts in these fields, including collecting human gaze data sets, modeling gaze behaviors, and utilizing gaze information in various applications, with the goal of enhancing communication between these research areas. We discuss future challenges and potential applications that work towards a common goal of human-centered artificial intelligence.

Keywords

  • Human aspects in AI: general
  • Machine Learning: general
  • Vision: general
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