CONF FunesMora_CVPR_2014/IDIAP Geometric Generative Gaze Estimation (G3E) for Remote RGB-D Cameras Funes Mora, Kenneth Alberto Odobez, Jean-Marc Gaze estimation generative models geometric method remote RGB-D segmentation variational inference EXTERNAL http://publications.idiap.ch/attachments/papers/2014/FunesMora_CVPR_2014.pdf PUBLIC IEEE Computer Vision and Pattern Recognition Conference Columbus, Ohio,USA 2014 IEEE 1773-1780 10.1109/CVPR.2014.229 doi We propose a head pose invariant gaze estimation model for distant RGB-D cameras. It relies on a geometric understanding of the 3D gaze action and generation of eye images. By introducing a semantic segmentation of the eye region within a generative process, the model (i) avoids the critical feature tracking of geometrical approaches requiring high resolution images; (ii) decouples the person dependent geometry from the ambient conditions, allowing adaptation to different conditions without retraining. Priors in the generative framework are adequate for training from few samples. In addition, the model is capable of gaze extrapolation allowing for less restrictive training schemes. Comparisons with state of the art methods validate these properties which make our method highly valuable for addressing many diverse tasks in sociology, HRI and HCI.