Appearance-based methods with deep learning can predict the point of gaze by using a monocular camera, which requires a large number of samples to learn. However, the samples collected in publicly available gaze
proposed the first deep CNN for gaze estimation in the wild [49, 51], which improved accuracy significantly. To further improve the accuracy, researchers have proposed en- hancements, such as employing the information outside the eye region [19, 50], fo...
Fig. 1: Overview of GazeNet – appearance-based gaze estimation using a deep convolutional neural network (CNN). across multiple datasets. This work aims to shed light on these questions and make the next step towards unconstrained gaze estimation. To facilitate cross-dataset evaluations, we fi...
and facial appearance variation. We show that image resolution and the use of both eyes affect gaze estimation performance while head pose and pupil centre information are less informative. Finally, we propose GazeNet, the first deep appearance-based gaze estimation method. GazeNet improves the state...
Paper tables with annotated results for Offset Calibration for Appearance-Based Gaze Estimation via Gaze Decomposition
high-frame rate head-mounted virtual reality system, can be leveraged to enhance the accuracy of an end-to-end appearance-based deep-learning model for gaze estimation. Performance is compared against a static-only version of the model. Results demonstrate statistically-significant benefits of tempora...
while head pose and pupil centre information are less informative. Finally, we propose GazeNet, the first deep appearance-based gaze estimation method. GazeNet improves on the state of the art by 22 percent (from a mean error of 13.9 degrees to 10.8 degrees) for the most challenging cross-dat...
Gaze estimation A 3D coordinate system with the camera center as the origin is first established, then a 3D eye model is established by landmarks of the eye, and the center coordinates of the eye sphere and the center coordinates of the pupil are calculated. The 3D vector from the center...
Appearance-based gaze estimation with deep learning: A review and benchmark. IEEE Trans. Pattern Anal. Mach. Intell. 2024, 1–20. [Google Scholar] [CrossRef] [PubMed] Perez, L.; Wang, J. The effectiveness of data augmentation in image classification using deep learning. arXiv 2017, ar...
the user's dominant eye for the purpose of gaze estimation, and point-of-regard mapping onto a 2D plane, achieved through an end-to-end training of an eye selector agent with domain-expertise knowledge embedded in an unsupervised manner via a convolutional deep neural network training process....