Camera distance from face images
Research output: Contribution to journal › Conference article › Research › peer-review
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.
Original language | English |
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Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Issue number | PART 2 |
Pages (from-to) | 513-522 |
Number of pages | 10 |
ISSN | 0302-9743 |
DOIs | |
Publication status | Published - 2013 |
Externally published | Yes |
Event | 9th International Symposium on Advances in Visual Computing, ISVC 2013 - Rethymnon, Crete, Greece Duration: 29 Jul 2013 → 31 Jul 2013 |
Conference
Conference | 9th International Symposium on Advances in Visual Computing, ISVC 2013 |
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Country | Greece |
City | Rethymnon, Crete |
Period | 29/07/2013 → 31/07/2013 |
Sponsor | BAE Systems, Intel, Ford, Hewlett-Packard, Mitsubishi Electric Research Labs |
ID: 302046971