Appearance-Based Gaze Estimation via Uncalibrated Gaze Pattern Recovery
Appearance-Based Gaze Estimation via Uncalibrated Gaze Pattern Recovery
复制标题
通过未校准的注视模式恢复进行基于外观的注视估计
DOI：
10.1109/tip.2017.2657880
复制
发表时间：
2017-04-01
影响因子：
10.6
通讯作者：
Sato, Yoichi
中科院分区：
文献类型：
--
作者：
Lu, Feng;Chen, Xiaowu;Sato, Yoichi
为了减少由于人/场景依赖而造成的限制，我们提出了一种新颖的方法，以一种新颖的方式解决基于外观的凝视估计。首先，我们引入并解决了独立于人和场景的眼睛图像的“未校准凝视模式”。通过非线性降维和像素运动分析，凝视模式恢复凝视运动，直到缩放和平移歧义，而不需要训练/校准。这在文献中是新的，可以实现新的应用。其次，我们的方法允许简单的校准，使凝视模式对准任何凝视目标。这比传统的校准要简单得多，传统的校准依赖于足够的训练数据来计算人和场景特定的非线性凝视映射。通过各种评估，我们表明：1)提出的无校准凝视模式具有新颖和广泛的功能；2)所提出的校准方法简单有效，在某些情况下甚至可以省略；定量评价在各种条件下都取得了令人满意的结果。
Aiming at reducing the restrictions due to person/scene dependence, we deliver a novel method that solves appearance-based gaze estimation in a novel fashion. First, we introduce and solve an "uncalibrated gaze pattern" solely from eye images independent of the person and scene. The gaze pattern recovers gaze movements up to only scaling and translation ambiguities, via nonlinear dimension reduction and pixel motion analysis, while no training/calibration is needed. This is new in the literature and enables novel applications. Second, our method allows simple calibrations to align the gaze pattern to any gaze target. This is much simpler than conventional calibrations which rely on sufficient training data to compute person and scene-specific nonlinear gaze mappings. Through various evaluations, we show that: 1) the proposed uncalibrated gaze pattern has novel and broad capabilities; 2) the proposed calibration is simple and efficient, and can be even omitted in some scenarios; and 3) quantitative evaluations produce promising results under various conditions.