Name
Abstract | ||
|---|---|---|
In this paper, we present an architecture of a system which aims to personalize the TV content to the viewer reactions. The focus of the paper is on a subset of this system which identifies moments of attentive focus in a non-invasive and continuous way. The attentive focus is used to dynamically improve the user profile by detecting which displayed media or links have drawn the user attention. Our method is based on the detection and estimation of face pose in 3D using a consumer depth camera. Two preliminary experiments were carried out to test the method and to show its link to viewer interest. This study is realized in the scenario of a TV with a second screen interaction (tablet, smartphone), a behaviour that has become common for spectators. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-319-03892-6_7 | Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering |
Keywords | Field | DocType |
attention,head pose estimation,second screen interaction,eye tracking,Facelab,future TV,personalization | Architecture,User profile,Computer science,Pose,Second screen,Human–computer interaction,Eye tracking,Multimedia,Personalization | Conference |
Volume | ISSN | Citations |
124 | 1867-8211 | 4 |
PageRank | References | Authors |
0.56 | 10 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julien Leroy | 1 | 53 | 10.28 |
| François Rocca | 2 | 14 | 3.10 |
| Matei Mancas | 3 | 315 | 27.50 |
| Bernard Gosselin | 4 | 198 | 12.88 |