ARTICLE FunesMora_IJCV_2015/IDIAP Gaze Estimation in the 3D Space Using RGB-D sensors. Towards Head-Pose And User Invariance. Funes Mora, Kenneth Alberto Odobez, Jean-Marc appearance based methods Gaze estimation head-pose invariance person invariance RGB-D cameras EXTERNAL http://publications.idiap.ch/attachments/papers/2015/FunesMora_IJCV_2015.pdf PUBLIC International Journal of Computer Vision 118 2 194-216 0920-5691 2016 First online: 13 November 2015 http://link.springer.com/article/10.1007/s11263-015-0863-4 URL 10.1007/s11263-015-0863-4 doi We address the problem of 3D gaze estimation within a 3D environment from remote sensors, which is highly valuable for applications in human-human and human-robot interactions. To the contrary of most previous works, which are limited to screen gazing applications, we propose to leverage the depth data of RGB-D cameras to perform an accurate head pose tracking, acquire head pose invariance through a 3D rectification process that renders head pose dependent eye images into a canonical viewpoint, and computes the line-of-sight in the 3D space. To address the low resolution issue of the eye image resulting from the use of remote sensors, we rely on the appearance based gaze estimation paradigm, which has demonstrated robustness against this factor. In this context, we do a comparative study of recent appearance based strategies within our framework, study the generalization of these methods to unseen individual, and propose a cross-user eye image alignment technique relying on the direct registration of gaze-synchronized eye images. We demonstrate the validity of our approach through extensive gaze estimation experiments on a public dataset as well as a gaze coding task applied to natural job interviews.