注视估计研究综述

Xiaomeng Wang, Kang Liu, Xu Qian
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引用次数: 12

摘要

眼向包含了大量的重要信息,可以用来估计使用者的意图和目的。在统计学、生物统计学、组织行为学等领域对注视方向进行了大量的研究并得到了完善。注视方法的细节是实现人机交互控制、人的意图预测、表情分析、认知状态分析等的必要条件。虽然近几十年来取得了积极而显著的进展,但眼睛检测仍然存在着位置偏差、尺度变异性、眼睛的个性、摄像机的复杂性、人及其相关仪器的校准、头部姿势的固定等挑战。本文对凝视估计进行了讨论,并提出了各种凝视检测和跟踪模型,这表明目前的理论需要进一步改进,以改进计算机视觉及其他领域的通用凝视跟踪估计方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Gaze Estimation
Eye orientation contains abundance of significant information for estimating user's intention and purpose. Large number of research on gaze direction has been given and improved in statistics, biometrics, organizational behavior, etc. Details of gaze methods are essential conditions for human-computer interactive control, human intention prediction, expression analysis, cognitive state analysis, etc. Although active and significant progress in last decades, eye detection still remains challenging to deviation of location, variability in scale, individuality of eyes, complexity of cameral, calibration of person and related instruments, fixation of head pose. In this paper, gaze estimation has been discussed and various models of gaze detection and tracking have been presented, which show current theoretical need to be further modified in order to improve general gaze tracking estimation solutions in computer vision and beyond.
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