Appearance-Based Gaze Tracking: A Brief Review

被引：11
作者：
Jiang, Jiaqi [1 ]
Zhou, Xiaolong [1 ,2 ]
Chan, Sixian [1 ]
Chen, Shengyong [1 ,3 ]
机构：
[1] Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou, Peoples R China
[2] Quzhou Univ, Coll Elect & Informat Engn, Quzhou, Peoples R China
[3] Tianjin Univ Technol, Sch Comp Commun & Engn, Tianjin, Peoples R China
来源：
INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2019, PART VI | 2019年 / 11745卷
基金：
中国国家自然科学基金; 国家重点研发计划;
关键词：
Gaze tracking; HCI; Appearance-based; Mapping; DIRECTION;
D O I：
10.1007/978-3-030-27529-7_53
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Human gaze tracking plays an important role in the field of Human-Computer Interaction. This paper presents a brief review on appearance-based gaze tracking. Based on the appearance of human eyes, input features can be classified into three categories according to the different ways of extracting human eyes features, namely, complete human eye image, pixel-based feature and 3D reconstruction image. The estimation process from human eye feature to fixation point mainly uses different mapping functions. In this paper, common mapping functions and related algorithms are described in detail: k-nearest neighbor (KNN), random forest (RF) regression, gaussian process (GP) regression, support vector machines (SVM) and artificial neural networks (ANN). This paper evaluates the performance of these gaze tracking algorithms using different mapping functions. Based on the results of the evaluation, potential challenges are summarized and the future directions of gaze estimation are prospected.
引用
收藏
页码：629 / 640
页数：12
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