Name
Abstract | ||
|---|---|---|
A novel approach to view-based eye gaze tracking for human computer interface (HCI) is presented. The proposed method combines different techniques to address the problems of head motion, illumination and usability in the framework of low cost applications. Feature detection and tracking algorithms have been designed to obtain an automatic setup and strengthen the robustness to light conditions. An extensive analysis of neural solutions has been performed to deal with the non-linearity associated with gaze mapping under free-head conditions. No specific hardware, such as infrared illumination or high-resolution cameras, is needed, rather a simple commercial webcam working in visible light spectrum suffices. The system is able to classify the gaze direction of the user over a 15-zone graphical interface, with a success rate of 95% and a global accuracy of around 2 degrees , comparable with the vast majority of existing remote gaze trackers. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.cmpb.2008.06.008 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
15-zone graphical interface,neural-based remote eye,extensive analysis,human computer interface,feature detection,different technique,natural head motion,infrared illumination,light condition,automatic setup,free-head condition,visible light spectrum suffices,spectrum,eye gaze,neural network,graphical interface,neural networks,infrared,visible light | Computer vision,BitTorrent tracker,Feature detection,Gaze,Computer science,Usability,Robustness (computer science),Eye tracking,Graphical user interface,Artificial intelligence,Artificial neural network | Journal |
Volume | Issue | ISSN |
92 | 1 | 0169-2607 |
Citations | PageRank | References |
21 | 1.08 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diego Torricelli | 1 | 57 | 9.97 |
| Silvia Conforto | 2 | 94 | 19.87 |
| Maurizio Schmid | 3 | 89 | 16.32 |
| Tommaso D'Alessio | 4 | 58 | 8.46 |