Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye’s movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.
|Title of host publication||Biologically Motivated Computer Vision - 2nd International Workshop, BMCV 2002, Proceedings|
|Editors||Heinrich H. Bulthoff, Christian Wallraven, Seong-Whan Lee, Tomaso A. Poggio|
|Number of pages||9|
|Publication status||Published - 2002|
|Event||2nd International Workshop on Biologically Motivated Computer Vision, BMCV 2002 - Tubingen, Germany|
Duration: 2002 Nov 22 → 2002 Nov 24
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||2nd International Workshop on Biologically Motivated Computer Vision, BMCV 2002|
|Period||02/11/22 → 02/11/24|
Bibliographical notePublisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)