Name
Abstract | ||
|---|---|---|
We present a method for estimating the distance between a camera and a human head in 2D images from a calibrated camera. Leading head pose estimation algorithms focus mainly on head orientation (yaw, pitch, and roll) and translations perpendicular to the camera principal axis. Our contribution is a system that can estimate head pose under large translations parallel to the camera's principal axis. Our method uses a set of exemplar 3D human heads to estimate the distance between a camera and a previously unseen head. The distance is estimated by solving for the camera pose using Effective Perspective n-Point (EPnP). We present promising experimental results using the Texas 3D Face Recognition Database. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-41939-3_50 | ADVANCES IN VISUAL COMPUTING, PT II |
Field | DocType | Volume |
Computer vision,Facial recognition system,Perpendicular,Pattern recognition,Computer science,Camera auto-calibration,Principal axis theorem,Pose,Camera resectioning,Artificial intelligence,Head tracking,Human head | Conference | 8034 |
ISSN | Citations | PageRank |
0302-9743 | 5 | 0.54 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arturo Flores | 1 | 8 | 0.92 |
| Eric M. Christiansen | 2 | 64 | 4.61 |
| David Kriegman | 3 | 7693 | 451.96 |
| Serge J. Belongie | 4 | 12512 | 1010.13 |