论文标题
ETH-XGAZE：一个大型数据集，用于在极端的头部姿势和凝视变化下进行凝视估算
ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation
论文作者
论文摘要
在计算机视觉，人类计算机交互和机器人技术的许多应用中，凝视估计是一项基本任务。在自定义数据集上对许多最先进的方法进行了培训和测试，从而使方法具有挑战性。此外，现有的凝视估计数据集的头部姿势和凝视变化有限，并且使用不同的协议和指标进行评估。在本文中，我们提出了一个新的凝视估计数据集，称为eth-xgaze，其中包括超过一百万个高分辨率的高分辨率图像，这些图像在极端的头部姿势下各种凝视。我们从110名参与者中收集了具有自定义硬件设置的参与者，包括18个数字SLR摄像头和可调节的照明条件，以及校准的系统以记录地面真相凝视目标。我们表明，我们的数据集可以显着提高不同头部姿势和凝视角度凝视估计方法的鲁棒性。此外，我们定义了ETH-XGAZE上的标准化实验方案和评估指标，以更好地统一凝视估计研究。数据集和基准网站可在https://ait.ethz.ch/projects/2020/eth-xgaze上找到
Gaze estimation is a fundamental task in many applications of computer vision, human computer interaction and robotics. Many state-of-the-art methods are trained and tested on custom datasets, making comparison across methods challenging. Furthermore, existing gaze estimation datasets have limited head pose and gaze variations, and the evaluations are conducted using different protocols and metrics. In this paper, we propose a new gaze estimation dataset called ETH-XGaze, consisting of over one million high-resolution images of varying gaze under extreme head poses. We collect this dataset from 110 participants with a custom hardware setup including 18 digital SLR cameras and adjustable illumination conditions, and a calibrated system to record ground truth gaze targets. We show that our dataset can significantly improve the robustness of gaze estimation methods across different head poses and gaze angles. Additionally, we define a standardized experimental protocol and evaluation metric on ETH-XGaze, to better unify gaze estimation research going forward. The dataset and benchmark website are available at https://ait.ethz.ch/projects/2020/ETH-XGaze
