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| Content Provider | Springer Nature Link |
|---|---|
| Author | Funes Mora, Kenneth A. Odobez, Jean Marc |
| Copyright Year | 2015 |
| Abstract | 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. |
| Starting Page | 194 |
| Ending Page | 216 |
| Page Count | 23 |
| File Format | |
| ISSN | 09205691 |
| Journal | International Journal of Computer Vision |
| Volume Number | 118 |
| Issue Number | 2 |
| e-ISSN | 15731405 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2015-11-13 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Gaze estimation Appearance based methods RGB-D cameras Head-pose invariance Person invariance Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Image Processing and Computer Vision Pattern Recognition |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Computer Vision and Pattern Recognition Software |
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